Fuzzy Logic

Mathematical Problems in Engineering, 2015

Since the ancient times, it has been assumed that categorization has the basic form of classical sets. This implies that the categorization process rests on the Boolean laws. In the second half of the twentieth century, the classical theory has been challenged in cognitive science. According to the prototype theory, objects belong to categories with intensities, while humans categorize objects by comparing them to prototypes of relevant categories. Such categorization process is governed by the principles of perceived world structure and cognitive economy. Approaching the prototype theory by using truth-functional fuzzy logic has been harshly criticized due to not satisfying the complementation laws. In this paper, the prototype theory is approached by using structure-functional fuzzy logic, the interpolative Boolean algebra. The proposed formalism is within the Boolean frame. Categories are represented as fuzzy sets of objects, while comparisons between objects and prototypes are formalized by using Boolean consistent fuzzy relations. Such relations are directly constructed from a Boolean consistent fuzzy partial order relation, which is treated by Boolean implication. The introduced formalism secures the principles of categorization showing that Boolean laws are fundamental in the categorization process. For illustration purposes, the artificial cognitive system which mimics human categorization activity is proposed.

PloS one, 2015

To understand the proximate and ultimate causes that shape acoustic communication in animals, objective characterizations of the vocal repertoire of a given species are critical, as they provide the foundation for comparative analyses among individuals, populations and taxa. Progress in this field has been hampered by a lack of standard in methodology, however. One problem is that researchers may settle on different variables to characterize the calls, which may impact on the classification of calls. More important, there is no agreement how to best characterize the overall structure of the repertoire in terms of the amount of gradation within and between call types. Here, we address these challenges by examining 912 calls recorded from wild chacma baboons (Papio ursinus). We extracted 118 acoustic variables from spectrograms, from which we constructed different sets of acoustic features, containing 9, 38, and 118 variables; as well 19 factors derived from principal component analys...

Journal of Business Economics and Management, 2013

The paper deals with the stakeholder management especially giving focus on the organization's and stakeholder relationships issues. The purpose of the paper is to construct a new methodological approach by developing fuzzy logic model based on experts' knowledge for conceptual insights on possible solutions for measuring stakeholders' influence. The objective of the research includes identification of possible organizationstakeholder interactions considering stakeholders' influence according to such attributes/ factors as interest, power, benevolence, and reliability. The results reveal that fuzzy logic technique is a reliable and valid tool for modelling and visualizing knowledge about stakeholders' influence on the organization. Finally, the results were tested on the real business data concerning stakeholders' influence. A contribution of this paper is the application of fuzzy logic model to evaluate and/or predict stakeholders' influence to the issues the organization seeks to solve and to provide relevant information for the stakeholder relationships management.

Applied Intelligence, 2012

A fundamental problem for disabled or elderly people is to manage their homes while carrying out an almost normal life, which implies using and interacting with a number of home devices. Recent studies in smart homes have proposed methods to use a laser pointer for interacting with home devices, which represents a more user-friendly and less expensive home device control environment. However, detecting the laser spot on the original non-filtered images, using standard and non-expensive cameras, and considering real home environments with varying conditions, is currently an open problem.

Advances in Fuzzy Systems

The main purpose of this paper is to introduce the notion of m-polar h-morphism on m-polar fuzzy graphs. The action of m-polar h-morphism on m-polar fuzzy graphs is studied. Some elegant theorems on weak and coweak isomorphism are obtained. Also, some properties of highly irregular, edge regular, and totally edge regular m-polar fuzzy graphs are studied.

Arabian Journal of Geosciences, 2015

In the earth sciences modeling, a great deal of uncertainty is associated with interpretation of subsurface data. Drilling borehole is one of the best tools for subsurface exploration and data gathering. Uncertainty of ore reserve modeling can be reduced by intelligent design of complementary drillings between the primary boreholes. This paper introduces a new method for determination of number, as well as directional and dimensional properties of such additional drillings based on ore value and objective functions, by applying an interval threshold concept. The proposed method is verified in Choghart iron deposit, central Iran. After calculations of descriptive statistical parameters, followed by geostatistical stages such as variography, anisotropy modeling, and kriging estimation of Fe (iron) and P (phosphorus) variables are performed. Thresholds commonly separate data sets into two classes by a sharp boundary and assigning samples to these indicators involve uncertainty. Instead of point threshold, an interval threshold with fuzzy membership function was implemented. Interval threshold is applied to determine indicators by considering Fe and P grades of kriging (soft) outputs. On the basis of one threshold for Fe and two thresholds for P, six classes of combination indicators of Fe and P were generated. Indicator-weighted average (IWA) and class membership degrees (CMD) for each block (sample) were measured by interval thresholds. Fe and P preference functions were defined for modeling of positive, neutral, and negative values (behaviors) in different ranges of grades. Ore value function is defined as a function of CMD, preference degrees, and weight factors for Fe and P grades. Finally, multiplicative equation of the ore value function and kriging variance is computed as objective function. Given large amounts of the objective function, four vertical and a single-directional drilling along with approximate length, priority of locations, azimuth, and dip angles of drillings are the final output of this method.

Sustainability

The aim of the study is to create a performance evaluation controlling model to evaluate the performance of tourism enterprises as a function of the economic effects of COVID-19. As a result of the significant change in demand resulting from the economic environment, expectations and cyclicality caused by the pandemic, the assessment of organization performance has become subjective. Under these changed environmental conditions, most of the methods used by tourism companies to evaluate performance are not effective enough. In our research, we illustrated a controlling model based on fuzzy logic through a case study. By applying the model, it becomes possible to evaluate project-oriented tourism organizations according to different standardized norms. Our model considers the subjectivity derived from measurability and goal setting. We point out that the performance of organizations operating in the tourism industry significantly influenced by COVID-19 can be subjectively assessed dur...

Construction Research Congress 2014, 2014

This version may not include final proof corrections and does not include published layout or pagination.

Sustainability, 2020

The Smart Cities (SCs) models currently widely employed are identical and inconsiderate of Economics Driven (ED), Local Context (LC), and Sustainability (St) factors. These are key factors to driving, constructing, and developing smart cities. This paper presents a process wherein "the Local Smart Sustain Cities Model (LSSCsM)" is combined and modeled with Exploratory Factor Analysis technique (EFA) to design a smart city that fits the local features of a given area. This particular process creates a Smart Cities Model (SCsM) that has unique sustainability and local context factors. This paper also presents the smart cities Priority Action Ranking (PAR) process using Fuzzy Logic Decision Making (FLDM) to evaluate the strengths and weaknesses of each smart city economics driver and characteristic and prioritize the direction planning of each factor and characteristic. The resulting smart cities model can then be used as the foundation of sustainable smart cities that avoid the pitfall of using incompatible smart cities models as the base and consequently failing, thus avoiding the extravagant costs associated with an unsuccessful project of such scale.

Risks

Coronavirus disease 2019 (COVID-19) continues to spread rapidly all over the world challenging nearly all governments. The exact nature of COVID-19’s spread and risk factors for such a rapid spread are still imprecise as available data depend on confirmed cases only. This may result in an asymmetrically distributed burden among countries. There is an urgent need for developing a new technique or model to identify and analyze risk factors affecting such a spread. Fuzzy logic appears to be suitable for dealing with multi-risk groups with undefined data. The main purpose of this research was to develop a risk analysis model for COVID-19’s spread evaluation. Other objectives included identifying such risk factors aiming to find out reasons for such a fast spread. Nine risk groups were identified and 46 risk factors were categorized under these groups. The methodology in this study depended on identifying each risk factor by its probability of occurrence and its impact on viruses spreadi...

Brain Sciences

Over the last few decades, the Brain-Computer Interfaces have been gradually making their way to the epicenter of scientific interest. Many scientists from all around the world have contributed to the state of the art in this scientific domain by developing numerous tools and methods for brain signal acquisition and processing. Such a spectacular progress would not be achievable without accompanying technological development to equip the researchers with the proper devices providing what is absolutely necessary for any kind of discovery as the core of every analysis: the data reflecting the brain activity. The common effort has resulted in pushing the whole domain to the point where the communication between a human being and the external world through BCI interfaces is no longer science fiction but nowadays reality. In this work we present the most relevant aspects of the BCIs and all the milestones that have been made over nearly 50-year history of this research domain. We mention...

Sustainability

Satisfied customers are the main sustainability factor for the viability of any activity, and tourism has increasing relevance to the global economy and the economic development of many regions. In order to create better matches between tourist demands and preferences and the local supply, an understanding of tourists as decision makers is necessary. The aim of this work is to introduce a mathematical model that explains the decision-making process of tourists, other consumers, and tourism business managers. We used a mathematical model, taking into consideration the preferences of individuals and their strengths during the exploration and use of tourism resources. The integration of preferences into an IT tool provided extra support to the decisions of tourists and allowed better choices to be made in the execution of travel plans. In addition, the model can be used by resource managers. Understanding how tourists make decisions in each different situation can improve the allocatio...

PeerJ Computer Science

Breast cancer becomes the second major cause of death among women cancer patients worldwide. Based on research conducted in 2019, there are approximately 250,000 women across the United States diagnosed with invasive breast cancer each year. The prevention of breast cancer remains a challenge in the current world as the growth of breast cancer cells is a multistep process that involves multiple cell types. Early diagnosis and detection of breast cancer are among the greatest approaches to preventing cancer from spreading and increasing the survival rate. For more accurate and fast detection of breast cancer disease, automatic diagnostic methods are applied to conduct the breast cancer diagnosis. This paper proposed the fuzzy-ID3 (FID3) algorithm, a fuzzy decision tree as the classification method in breast cancer detection. This study aims to resolve the limitation of an existing method, ID3 algorithm that unable to classify the continuous-valued data and increase the classification...

Frontiers in Marine Science

With globally accelerating rates of environmental disturbance, coastal marine ecosystems are increasingly prone to non-linear regime shifts that result in a loss of ecosystem function and services. A lack of early-detection methods, and an over reliance on limits-based approaches means that these tipping points manifest as surprises. Consequently, marine ecosystems are notoriously difficult to manage, and scientists, managers, and policy makers are paralyzed in a spiral of ecosystem degradation. This paralysis is caused by the inherent need to quantify the risk and uncertainty that surrounds every decision. While progress toward forecasting tipping points is ongoing and important, an interim approach is desperately needed to enable scientists to make recommendations that are credible and defensible in the face of deep uncertainty. We discuss how current tools for developing risk assessments and scenario planning, coupled with expert opinions, can be adapted to bridge gaps in quantitative data, enabling scientists and managers to prepare for many plausible futures. We argue that these tools are currently underutilized in a marine cumulative effects context but offer a way to inform decisions in the interim while predictive models and early warning signals remain imperfect. This approach will require redefining the way we think about managing for ecological surprise to include actions that not only limit drivers of tipping points but increase socio-ecological resilience to yield satisfactory outcomes under multiple possible futures that are inherently uncertain.

International Journal of Technology Diffusion, 2011

Many organizations attempt to form strategic networked enterprises, yet such strategies are difficult to implement because they are as likely to fail as to succeed. This failure is due to intangible differences and mismatches between partners in tacit knowledge (TK). Despite the various proposed partnership assessment models/tools in the literature, an immediate need exists for a new approach to measure the mismatch in TK across different organizations. This is due to the complex, vague, and uncertain nature of TK attributes. Hence, an instrument for measuring vagueness (imprecise), such as fuzzy linguistic variables, is needed. In this study, the author applies a neuro-fuzzy approach to assess TK fitness in networked enterprises. The results show how differences in TK between partners affect the networked enterprise’s performance. Furthermore, the assessment approach reveals the most significant values to adopt and the irrelevant values that must be abandoned to smooth the partners...

Artificial Intelligence Review, 2013

The application of artificial intelligence (AI) techniques in modeling of machining process has been investigated by many researchers. Fuzzy logic (FL) as a well-known AI technique is effectively used in modeling of machining processes such as to predict the surface roughness and to control the cutting force in various machining processes. This paper is started with the introduction to definition of FL and machining process, and their relation. This paper then presents five types of analysis conducted on FL techniques used in machining process. FL was considered for prediction, selection, monitoring, control and optimization of machining process. Literature showed that milling contributed the highest number of machining operation that was modeled using FL. In terms of machining performance, surface roughness was mostly studied with FL model. In terms of fuzzy components, center of gravity method was mostly used to perform defuzzification, and triangular was mostly considered to perform membership function. The reviews extend the analysis on the abilities, limitations and effectual modifications of FL in modeling based on the comments from previous works that conduct experiment using FL in the modeling and review by few authors. The analysis leads the author to conclude that FL is the most popular AI techniques used in modeling of machining process.

Philosophies

Statistical Hypothesis Testing (SHT) is a class of inference methods whereby one makes use of empirical data to test a hypothesis and often emit a judgment about whether to reject it or not. In this paper, we focus on the logical aspect of this strategy, which is largely independent of the adopted school of thought, at least within the various frequentist approaches. We identify SHT as taking the form of an unsound argument from Modus Tollens in classical logic, and, in order to rescue SHT from this difficulty, we propose that it can instead be grounded in t-norm based fuzzy logics. We reformulate the frequentists’ SHT logic by making use of a fuzzy extension of Modus Tollens to develop a model of truth valuation for its premises. Importantly, we show that it is possible to preserve the soundness of Modus Tollens by exploring the various conventions involved with constructing fuzzy negations and fuzzy implications (namely, the S and R conventions). We find that under the S conventio...

International Journal of Environmental Science and Technology, 2013

Supplier evaluation problems deal with selecting appropriate suppliers considering multiple criteria, which may be related with qualitative and quantitative aspects. Traditional supplier selection criteria contain criteria such as cost, capacity, delivery reliability, flexibility, and responsiveness, etc. However, due to the increasing level of environmental problems, it is a necessity to take environmental criteria into account together with the traditional decision criteria in the supplier evaluation processes of companies. Considering this necessity, this paper proposes a decision making methodology for environmental criteria integrated supplier evaluation processes. A methodology based on intuitionistic fuzzy Choquet integral operator is utilized to take into account vagueness of the decision environment and the interactions among the criteria. This methodology also provides the consideration of the satisfaction and dissatisfaction degrees of alternatives for each criterion with the help of intuitionistic fuzzy values. In addition, the effects of the criteria weights to the final ranking of suppliers are analyzed via sensitivity analyses.

2020

Performance is one of the major topics for organizations seeking continuous improvements. Evidently, evaluating the performance of business process model is a necessary step to reduce time, cost and to indicate whether the company goals are successfully achieved or not. In the literature, several researchers refers to different techniques that aim at improving a BP model performance. Some approaches assist BP designers to develop high-performance models while others propose measures to assess the performance. This paper adopts performance measures and targets models represented in Business Process Modeling and Notation (BPMN). It proposes a methodology based on fuzzy logic along with a tool system developed under eclipse to evaluate the performance of business process models in terms of characteristics related to the actor (i.e. availability, suitability and cost) and characteristics related to BPMN elements (i.e. time behaviour, cost). The preliminary experimental evaluation of the proposed system shows encouraging results.

Transport Reviews, 2015

The paper examines similarities and differences in public private partnership (PPP) structures between airports and seaports in low and middle income countries using data from the World Bank's Private Participation in Infrastructure (PPIAF) database, and puts forward some hypotheses about the reasons for the differences. Qualification of the results is also made with available literature on airport and seaport PPPs. It uses eight granules-the eight 'Ws'-as the basis for the analysis, comparing PPPs in terms of 'What', 'When', 'Where', 'Why', 'Whole', 'Who', 'Whom', and 'Which way'. Although the similarities between port and airport PPPs generally outweigh their differences, there are several areas in which they diverge. These are the characteristics of private sector partner, the PPP models used, the use made of competitive tendering, and the bundling of facilities. Airport investors tend to attract a wider array of investor types than seaports, where the focus is more on specialized operators in BOT agreements. These differences have their roots in four main structural variations between the two industries: the level of integration of infrastructure and services, economies of scale, public service obligations, and the differing roles of competition and regulation.

Applied Sciences

In the preliminary stages of design of the oscillating water column (OWC) type of wave energy converters (WECs), we need a reliable cost- and time-effective method to predict the hydrodynamic efficiency as a function of the design parameters. One of the cheapest approaches is to create a multiple linear regression (MLR) model using an existing data set. The problem with this approach is that the reliability of the MLR predictions depend on the validity of the regression assumptions, which are either rarely tested or tested using sub-optimal procedures. We offer a series of novel methods for assumption diagnostics that we apply in our case study for MLR prediction of the hydrodynamics efficiency of OWC WECs. Namely, we propose: a novel procedure for reliable identification of the zero singular values of a matrix; a modified algorithm for stepwise regression; a modified algorithm to detect heteroskedasticity and identify statistically significant but practically insignificant heterosc...

Energies

The paper presents the design and the implementation of different advanced control strategies that are applied to a nonlinear model of a thermal unit. A data-driven grey-box identification approach provided the physically-meaningful nonlinear continuous-time model, which represents the benchmark exploited in this work. The control problem of this thermal unit is important, since it constitutes the key element of passive air conditioning systems. The advanced control schemes analysed in this paper are used to regulate the outflow air temperature of the thermal unit by exploiting the inflow air speed, whilst the inflow air temperature is considered as an external disturbance. The reliability and robustness issues of the suggested control methodologies are verified with a Monte Carlo (MC) analysis for simulating modelling uncertainty, disturbance and measurement errors. The achieved results serve to demonstrate the effectiveness and the viable application of the suggested control solutions to air conditioning systems. The benchmark model represents one of the key issues of this study, which is exploited for benchmarking different model-based and data-driven advanced control methodologies through extensive simulations. Moreover, this work highlights the main features of the proposed control schemes, while providing practitioners and heating, ventilating and air conditioning engineers with tools to design robust control strategies for air conditioning systems.

Freshwater Science, 2017

The Biological Condition Gradient (BCG) is a conceptual model that describes changes in aquatic communities with increasing levels of anthropogenic stress. The gradient represented by the BCG has been divided into 6 levels of condition that biologists consider readily discernible in most areas of North America. We developed quantitative BCG models for 7 warm-water stream types in Minnesota for both fish and macroinvertebrates. Panels of aquatic biologists calibrated the general BCG model to Minnesota streams by assigning test samples (271 macroinvertebrate and 288 fish samples) to BCG Levels 1 to 6. From the panelists' descriptions of their criteria for assigning sites to levels, a set of quantitative operational rules was developed for performing the same task. We developed a decision model based on fuzzy-set theory to account for discontinuities and to identify when BCG assignments might be intermediate between adjacent levels. This model captures the consensus professional judgment of the panel and uses panel-derived rules. Decisions based on the quantitative model for macroinvertebrates exactly matched 77% of the panel decisions, 89% within ½ BCG level, and 100% within 1 BCG level. Decisions based on the quantitative fish model exactly matched 70% of the panel decisions, 86% within ½ BCG level, and 99% within 1 BCG level. The BCG provides a tool to interpret aquatic biological condition along a gradient of naturalness and is consistent across stream types and political boundaries. It includes documentation of baselines to prevent inadvertent shifting, and the BCG logic rules are transparent, a desirable property for communicating condition, management goals, and water-quality criteria.

Engineering, Technology & Applied Science Research

The majority of leader companies are running their businesses using online E-commerce websites. These E-commerce websites are becoming significant revenue drivers and major retailers. Hence, it is critical to evaluate the functionality of these websites which are expected to support growing business needs. The evaluation of the functionality of E-commerce websites is not a straightforward process due to the many constraints and standards that should be considered. Fuzzy logic is a powerful technique used in modeling impreciseness and uncertainties. This paper proposes a Mamdani fuzzy system that evaluates the functionality of E-commerce websites over different parameters: accuracy, flexibility, client support, and availability of product information. Experimental results provide positive relations between accuracy and flexibility on the functionality of E-commerce websites.

American Journal of Primatology, 2021

Human vocal ontogeny is considered to be a process whereby a large repertoire of discrete sounds seemingly emerges from a smaller number of acoustically graded vocalizations. While adult chimpanzee vocal behavior is highly graded, its developmental trajectory is poorly understood. In the present study, we therefore examined the size and structure of the chimpanzee vocal repertoire at different stages of ontogeny. Audio recordings were collected on infant (N = 13) and juvenile (N = 13) semi‐wild chimpanzees at Chimfunshi Wildlife Orphanage, Zambia, using focal and ad libitum sampling. All observed call types were acoustically measured. These were predominantly grunts, whimpers, laughs, screams, hoos, and barks and squeaks. A range of spectral and temporal acoustic parameters were extracted, and fuzzy c‐means clustering was used to quantify the size and structure of the repertoire. The infant and juvenile vocal repertoires were both best described with the same number of clusters. How...

Advances in Computational Intelligence and Robotics

CPU Scheduler is one of the crucial modules of any operating system. Operating system uses CPU schedulers based on the requirements. Fair Share CPU scheduler is preferable scheduler by many operating systems. It distributes fixed processor time amongst different parts of a system like groups, users etc. Fixed distribution of processor time can distress the performance of system. Moreover, traditional CPU schedulers ignore the impreciseness and uncertainty of the tasks. This work presents the Intuitionistic Fuzzy based Fair Share scheduler (IFFS). IFFS scheduler has extended the research in the field of the impreciseness of tasks. Intuitionistic Fuzzy Inference Systems, IFIS-DP and IFIS-DCS have been designed to share the CPU time dynamically and for assigning dynamic priority to each task. Experimental results prove the better performance of IFFS scheduler over FS scheduler. CPU SCHEDULER: MAIN MODULE OF AN OPERATING SYSTEM Operating System is a significant software component of any computer system. These software components are mainly divided into two categories,

Sensors

Infectious diseases are caused by pathogenic microorganisms, whose transmission can lead to global pandemics like COVID-19. Contact with contaminated surfaces or objects is one of the major channels of spreading infectious diseases among the community. Therefore, the typical contaminable surfaces, such as walls and handrails, should often be cleaned using disinfectants. Nevertheless, safety and efficiency are the major concerns of the utilization of human labor in this process. Thereby, attention has drifted toward developing robotic solutions for the disinfection of contaminable surfaces. A robot intended for disinfecting walls should be capable of following the wall concerned, while maintaining a given distance, to be effective. The ability to operate in an unknown environment while coping with uncertainties is crucial for a wall disinfection robot intended for deployment in public spaces. Therefore, this paper contributes to the state-of-the-art by proposing a novel method of est...

The International Journal of Advanced Manufacturing Technology, 2014

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Annals of Forest Science, 2017

& Key message Average soil moisture was spatially modelled for observed periods and climate scenarios using a fuzzy logic approach. Accordingly, a significant decline of soil moisture until 2070 in Germany and the Kellerwald National Park could be evidenced for soils influenced by ground water and by stagnant water and at sites on steep slopes and on southerly slopes. & Context Soil moisture is an essential environmental factor affecting the condition of forests throughout time with high spatial variance. To adapt forests to climate change, assessments of ecological integrity and services in forest management and nature conservation need spatio-temporal estimations of current and future soil moisture. Dynamic modelling of soil moisture even with rather simple models needs numerous data which are often not available for areas of large spatial extent. & Aims Therefore, the objectives of this investigation were to (1) spatio-temporally estimate ecological soil moisture with available data covering the whole territory of Germany, (2) to specify these estimates for the regional scale, (3) to statistically analyse temporal trends of modelled soil moisture for the time period 1961-2070 and (4) to map soil moisture changes (drying-out) at both national and regional levels. & Methods A fuzzy rule-based model was developed allowing the combination of a pedological and an ecological soil moisture classification. The fuzzy modelling approach was applied for mapping average soil moisture at two spatial scales. & Results Soil moisture was modelled and mapped on a scale of 1:500,000 across Germany and regionally specified on a scale of 1:25,000 for the Kellerwald National Park for the time

Applied Computational Intelligence and Soft Computing, 2014

In operating system the decisions which CPU scheduler makes regarding the sequence and length of time the task may run are not easy ones, as the scheduler has only a limited amount of information about the tasks. A good scheduler should be fair, maximizes throughput, and minimizes response time of system. A scheduler with multilevel queue scheduling partitions the ready queue into multiple queues. While assigning priorities, higher level queues always get more priorities over lower level queues. Unfortunately, sometimes lower priority tasks get starved, as the scheduler assures that the lower priority tasks may be scheduled only after the higher priority tasks. While making decisions scheduler is concerned only with one factor, that is, priority, but ignores other factors which may affect the performance of the system. With this concern, we propose a 2-layered architecture of multilevel queue scheduler based on vague set theory (VMLQ). The VMLQ scheduler handles the impreciseness of data as well as improving the starvation problem of lower priority tasks. This work also optimizes the performance metrics and improves the response time of system. The performance is evaluated through simulation using MatLab. Simulation results prove that the VMLQ scheduler performs better than the classical multilevel queue scheduler and fuzzy based multilevel queue scheduler.

Journal of Function Spaces, 2022

Vague incidence graph (VIG), belonging to the FG family has good capabilities when facing with problems that cannot be expressed by FGs. When an element membership is not clear, neutrality is a good option that can be well-supported by a VIG. The previous definitions limitations in connectivity concept have led us to offer new definitions in VIGs. Hence, in this paper, the VIG and its matrix form are proposed. Vague incidence subgraph (VISG) is defined with several properties. Incidence pairs, paths, and connectivities between pairs in VIGs are introduced. Likewise, different types of strong and cut pair in VIGs are examined with their properties. Universities are one of the most important centers for human education and play an important role in the development of the country. But the point to be very careful is that the employees of a university must do their job in the best possible way. Therefore, we have tried to identify the most effective person in a university according to i...

Water, 2022

In order to guarantee the sustainability of the potable water supply service, a water utility must generate improvements in its performance in an integrated manner. The objective of this research is to analyze and provide information about the components and indicators used by the water utility of Leon, Guanajuato, Mexico, which directly impact water management. The Analytic Hierarchy Process (AHP) and Fuzzy Logic (FL) methodologies were applied. The study determined the trends and evolution over time from 2002 to 2017. From the combination of both methodologies, a Water Supply Management Index was obtained with an average value of 0.79, which shows positive progress for water resource management by the water utility. However, the traditional indicators are insufficient and require particular attention. The analysis helped to identify those indicators that do impact water management and their ability to measure the sustainability of the city’s water utility. This may make it possibl...

Journal of Material Cycles and Waste Management, 2013

This paper shows the concept and preliminary test of the composting process control with fuzzy logic. The temperature in the compost heap during the process is greater than 80°C. Because wastes of agricultural origin do not require hygienization, part of the heat can by retrieved, which lowers the temperature in the heap to 55°C (this is also the optimum temperature for the composting process). The heat retrieved from a compost heap can be used in another place. Therefore, a composting system was developed in which the aeration rate and heat removal rate can be adjusted. There are two goals of this system: maximising the amount of the heat retrieved from the heap and minimising the duration of the composting process. In the preliminary experiments freshly mown grass with 50 % cabbage was used as the compost material. The results show that the fuzzy logic control system functions correctly with respect to calculations. During the study, a median 90 MJ of heat was produced by the bioreactor; the thermophilic phase was shortened to 12 days. There was also a reduction in the emission of ammonia.

Metrology and Measurement Systems, 2011

Two Heuristic Algorithms for Test Point Selection in Analog Circuit Diagnoses The paper presents a heuristic approach to the problem of analog circuit diagnosis. Different optimization techniques in the field of test point selection are discussed. Two new algorithms: SALTO and COSMO have been introduced. Both searching procedures have been implemented in a form of the expert system in PROLOG language. The proposed methodologies have been exemplified on benchmark circuits. The obtained results have been compared to the others achieved by different approaches in the field and the benefits of the proposed methodology have been emphasized. The inference engine of the heuristic algorithms has been presented and the expert system knowledge-base construction discussed.

Journal of Mathematics

Many problems of practical interest can be modeled and solved by using vague graph (VG) algorithms. Vague graphs, belonging to the fuzzy graphs (FGs) family, have good capabilities when faced with problems that cannot be expressed by FGs. Hence, in this paper, we introduce the notion of η , γ - HMs of VGs and classify homomorphisms (HMs), weak isomorphisms (WIs), and coweak isomorphisms (CWIs) of VGs by η , γ - HMs. Hospitals are very important organizations whose existence is directly related to the general health of the community. Hence, since the management in each ward of the hospital is very important, we have tried to determine the most effective person in a hospital based on the performance of its staff.

Mathematical Problems in Engineering, 2014

We consider a multiobjective linear fractional transportation problem (MLFTP) with several fractional criteria, such as, the maximization of the transport profitability like profit/cost or profit/time, and its two properties are source and destination. Our aim is to introduce MLFTP which has not been studied in literature before and to provide a fuzzy approach which obtain a compromise Pareto-optimal solution for this problem. To do this, first, we present a theorem which shows that MLFTP is always solvable. And then, reducing MLFTP to the Zimmermann’s “min” operator model which is the max-min problem, we construct Generalized Dinkelbach’s Algorithm for solving the obtained problem. Furthermore, we provide an illustrative numerical example to explain this fuzzy approach.

MATEC Web of Conferences

Bridges play important roles in transportation system. Hazard to substructure of bridges become amplified. Based on previous year data, at least one-third of total bridges in Indonesia are damaged in certain level of defect. The performance of existing bridges shall be in-check everytime. Substructure of bridge itself is prone to hazards such as ground displacement, slope instability, seismic-related hazard and scour. Traffic data and soil investigation data will be used to analyse ground displacement and slope instability where the bridge located. Local geological and seismic data will be used to assess seismic-related hazard. Quantitative data is technical information and analyses from geotechnical aspects. Qualitative data is an expert system collected from bridge expert and local goverment. The expert system will have a rating system for each aspect. Fuzzy-based method is an effective tool for modeling some vague datas and this ease the decision-making process. Fuzzy Analytical ...

Health and Technology, 2022

COVID-19 disease is an outbreak that seriously affected the whole world, occurred in December 2019, and thus was declared a global epidemic by WHO (World Health Organization). To reduce the impact of the epidemic on humans, it is important to detect the symptoms of the disease in a timely and accurate manner. Recently, several new variants of COVID-19 have been identified in the United Kingdom (UK), South Africa, Brazil and India, and preliminary findings have been suggested that these mutations increase the transmissibility of the virus. Therefore, the aim of this study is to construct a support system based on fuzzy logic for experts to help detect of COVID-19 infection risk in a timely and accurate manner and to get a numerical output on symptoms of the virus from every person. The decision support system consists of three different sub and one main Mamdani type fuzzy inference systems (FIS). Subsystems are Common- Serious symptoms (First), Rare Symptoms (Second) and Personal Inf...

Scientometrics, 2019

The development of a scientific discipline is partly determined by the growth of its literature. Bibliometrics constitute a set of mathematical and statistical techniques employed to explore, organize, and quantitatively analyze large pools of scientific literature. In this study, 11,433 papers published between 1974 and 2015 are collected and analyzed by applying life-cycle analysis, bibliometrics and text mining in order to provide a full thematic overview of the application of fuzzy theory in operations management. Top countries (i.e. the most productive, influential and collaborative countries), most frequently cited journals, and key research topics are identified by employing bibliometric techniques. Finally, the articles' common research themes and methodologies are determined by combining text mining with experts' input. Results show that the application of fuzzy theory in operations management is still in its infancy, and hence suitable for future research. This study serves as a guide for researchers to identify the hidden patterns, key actors, topics, and methods in this area.

International Journal of Computational Intelligence Systems, 2016

Fuzzy sets have a great progress in every scientific research area. It found many application areas in both theoretical and practical studies from engineering area to arts and humanities, from computer science to health sciences, and from life sciences to physical sciences. In this paper, a comprehensive literature review on the fuzzy set theory is realized. In the recent years, ordinary fuzzy sets have been extended to new types and these extensions have been used in many areas such as energy, medicine, material, economics and pharmacology sciences. This literature review also analyzes the chronological development of these extensions. In the last section of the paper, we present our interpretations on the future of fuzzy sets.

Journal of Sensor and Actuator Networks

The safety of various road users and vehicle passengers is very important in our increasingly populated roads and highways. To this end, the correct perception of driving conditions is imperative for a driver to react accordingly to a given driving situation. Various sensors are currently being used in recognizing driving context. To further enhance such driving environment perception, this paper proposes the use of UAVs (unmanned aerial vehicles, also known as drones). In this work, drones are equipped with sensors (radar, lidar, camera, etc.), capable of detecting obstacles, accidents, and the like. Due to their small size and capability to move places, drones can be used collect perception data and transmit them to the vehicle using a secure method, such as an RF, VLC, or hybrid communication protocol. These data obtained from different sources are then combined and processed using a knowledge base and some set of logical rules. The knowledge base is represented by ontology; it c...

Lecture Notes in Computer Science, 2009

We survey on the theoretical and practical developments of the theory of fuzzy logic and soft computing. Specifically, we briefly review the history and main milestones of fuzzy logic (in the wide sense), the more recent development of soft computing, and finalise by presenting a panoramic view of applications: from the most abstract to the most practical ones.

Materials, 2021

Air classifier devices have a distinct advantage over other systems used to separate materials. They maximize the mill’s capacity and therefore constitute efficient methods of reducing the energy consumption of crushing and grinding operations. Since improvement in their performance is challenging, the development of an efficient modeling system is of great practical significance. The paper introduces a novel, knowledge-based classification (FLClass) system of bulk materials. A wide range of operating parameters are considered in the study: the mean mass and the Sauter mean diameter of the fed material, classifier rotor speed, working air pressure, and test conducting time. The output variables are the Sauter mean diameter and the cut size of the classification product, as well as the performance of the process. The model was successfully validated against experimental data. The maximum relative error between the measured and predicted data is lower than 9%. The presented fuzzy-logi...

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 2011

The detection of diseases often can be formalized as a decision problem that typically has to be solved merging uncertain information; diagnostic tools, intended to aid the physician in interpreting the data, besides attaining the best possible correct classification rate, should furnish some insight into how the problem has been decided. Fuzzy logic is a well known successful attempt to automatize the human capability to reason with imperfect information; fuzzy systems are rule-based so that they can easily provide motivations for their decisions, after having verified some additional conditions. In this paper we describe a six-steps data driven methodology to automatically build fuzzy systems with a user defined number of rules; almost each step can be approached using several strategies and we thus describe an implementation of the proposed solution. Then, we test our systems on a well known and widely used data set of features of images of breast masses and, having the number of rules varying, we show results both in terms of correct classification rates and in terms of systems' confidence in the obtained decisions. Finally, we select the number of rules that produces the most interpretable and trustworthy system; such a system is described in details and tested.

Safety, 2020

In recent years, the focus in safety management has shifted from failure-based analysis towards a more systemic perspective, redefining a successful or failed performance as a complex and emergent event rather than as a conclusion of singular errors or root causes. This paradigm shift has also necessitated the introduction of innovative tools capable of capturing the complex and dynamic nature of modern sociotechnical systems. In our research, we argued at previous stages for adopting a more systemic and human-centric perspective to evaluate the context of aircraft de-icing operations. The Functional Resonance Analysis Method (FRAM) was applied in the first stage for this purpose. Consequently, fuzzy logic was combined with FRAM in the second stage to provide a quantified representation of performance variability. Fuzzy logic was used as a quantification tool suitable for computing with natural language. Several limitations were found in the data collection and rule generation proce...

Theory and Applications of Ordered Fuzzy Numbers, 2017

This chapter concerns an issue of comparing fuzzy numbers. The relationship of similarity is probably the most widely used and most difficult to determine the measure of compliance precisely. Analysis of the similarity between two objects is an essential tool in biology, taxonomy, and psychology, and is the basis for reasoning by analogy. This chapter describes methods for determining the similarity used in fuzzy logic. Many of them were dedicated only to triangular or trapezoidal fuzzy numbers. This was a computing inconvenience and raised the question about the axiological basis for such comparisons. The authors have proposed two new approaches to comparing fuzzy numbers using one of the known fuzzy number extensions that are Ordered Fuzzy Numbers (OFNs). This has allowed us to simplify operations and eliminate said dualism. Two order-sensitive defuzzification methods are presented in the chapter. For OFN numbers with positive order (compliant with the direction of the OX axis increase) the results of defuzzifications are results for numbers of different notations, for example, L-R, whereas for numbers with negative orders, the defuzzification result changes. An important part of the chapter is a catalogue of the shapes of numbers in OFN notation. This is probably the first summary of basic shapes of those numbers with the results of defuzzifications using several methods.

Information, 2020

The purpose of this extension of the ESM’2019 conference paper is to propose some means to implement an artificial thinking model that simulates human psychological behavior. The first necessary model is the time fuzzy vector space model (TFVS). Traditional fuzzy logic uses fuzzification/defuzzification, fuzzy rules and implication to assess and combine several significant attributes to make deductions. The originality of TFVS is not to be another fuzzy logic model but rather a fuzzy object-oriented model which implements a dynamic object structural, behavior analogy and which encapsulates time fuzzy vectors in the object components and their attributes. The second model is a fuzzy vector space object oriented model and method (FVSOOMM) that describes how-to realize step by step the appropriate TFVS from the ontology class diagram designed with the Unified Modeling Language (UML). The third contribution concerns the cognitive model (Emotion, Personality, Interactions, Knowledge (Con...

Information

This paper reviews the research on adaptive serious games for programming regarding the implementation of their support systems. Serious games are designed to educate players in an entertaining and engaging manner. A key element in terms of meeting their educational goals is the presentation of the learning content through a support system. Recent developments in artificial intelligence, data analysis, and computing made the development of support systems that adapt to player individual characteristics possible. A systematic literature review is necessary to evaluate the efficiency of adaptive supports and examine the implementation approaches. This review identified 18 papers reporting evidence about the efficiency of the provided support and methods of development. A variety of techniques for presenting educational content was found, with text being the preferred type. Researchers employed data-driven approaches to model student knowledge levels and behavior such as Bayesian netwo...

OPSEARCH, 2017

Partner selection is a crucial problem in supply chain management in which it is essential today to integrate sustainability criteria due to regulation, stakeholder pressers and economic interests. Thus, a sustainability-focused evaluation model for partner selection is required in order to improve the overall performance of the supply chain. This paper develops a new hybrid approach to evaluate and select the partners (suppliers and 3PRL providers) in sustainable supply chain network by combining Fuzzy Analytic Hierarchy Process (F-AHP) with Fuzzy Preference Ranking Organization Method for Enrichment Evaluation (F-PROMETHEE), and Fuzzy Technique for Order Performance by Similarity to Ideal Solution (F-TOPSIS). A set of sustainability criteria for both supplier and 3PRL provider selection is proposed based on extensive literature review and experts' opinions. F-AHP is used to calculate the priority weight of each criterion. Then, F-PROMETHEE and F-TOPSIS are both used to rank the partners comparatively. The validity and efficacy of the proposed approach is demonstrated through an application for selecting partners in the case of light bulbs recycling which has been strengthened by sensitivity analysis.

Civil and Environmental Engineering, 2021

Wastewater treatment plants (WWTPs) contain a large number of components, and these components in turn require a large number of maintenance activities and high costs. In this paper, a Fuzzy-based Multi-Criteria Decision Support System (FBMCDS) model was designed based on the failure mode and effect analysis FM-EA and applied to the Rustumiya Project (RP) in Iraq. Information of the RP’s components, failure modes, applied maintenance activities and costs were collected from the documented data, site visit and face-to-face interviews as well as opinions of 44 experts. Through applying the fuzzy logic to analysis the failure modes and effects, the risk priority index (FMRPI) and total intensity (FMTI) of each failure mode ware computed. Thus, maintenance priorities and weights of the RP’s failure modes were specified. In addition, the best maintenance plan was specified based on the FMRPI-FMTI diagram that shows the importance and the type of maintenance required for each failure mode...

Sliding-Mode Fuzzy Controllers, 2021

The word "fuzzy" means imprecisely defined, confused, and vague. Thus fuzzy logic is a precise logic of imprecision and approximate reasoning [37]. FLSs are systems to be precisely defined, and SMFC is a special kind of nonlinear control with precise formulation and well-established mathematical analysis [32]. Lotfi Zadeh proposed fuzzy logic in his paper entitled "fuzzy sets," which was published in the journal of Information and Control [36] as an extension to conventional logic, in which, the degree of membership of an input can be given any value from the interval of [0, 1] rather than the discrete values of zero and one. FLSs can deal with uncertainty and vagueness in real-time systems. Moreover, it has the possibility to represent human knowledge in terms of a system that can work independent of the expert. Fuzzy logic has been implemented in different applications during the last five decades. The first implementation of fuzzy logic as a controller on a real-time system dates back to 1975 when Mamdani and Assilian implemented [17, 32] fuzzy logic to control a steam engine. Fuji electric water purification plant in 1980, fuzzy robots, and the self-parking car were the first applications of FLSs in industry [30, 32]. 3.1.1 Fuzzy Logic and Control There are different requirements for a successful control system; the most important of which is stability. There exist different definitions for stability, from which, Lyapunov stability, asymptotic stability, and exponential stability are considered [10]. Moreover, the stability of the system can be local, which means that it is only valid for system state initial conditions that are located in a certain region. On the other hand, the system is globally stable, which means that it is stable regardless of its state initial values. Stability analysis of the system may impose different conditions

Journal of Logic, Language and Information, 2019

Development of decision-support and intelligent agent systems necessitates mathematical descriptions of uncertainty and fuzziness in order to model vagueness. This paper seeks to present an outline of Peirce's triadic logic as a practical new way to model vagueness in the context of artificial intelligence (AI). Charles Sanders Peirce (1839-1914) was an American scientist-philosopher and a great logician whose triadic logic is a culmination of the study of semiotics and the mathematical study of anti-Cantorean model of continuity and infinitesimals. After presenting Peircean semiotics within AI perspective, a mathematical formulation of a Peircean triadic set is given in relationship with classical and fuzzy sets. Using basic logical operators, all possible respective implication operators, bi-equivalence operators, valid rules of inference, and associative, distributive and commutative logical properties are derived and verified through the truth function approach. In order to suggest practical directions, aggregation operators for Peirce's triadic logic have been formulated. A mathematical formulation of a medical diagnostic problem and ER diagram of a library management system using Peirce's triadic relation show potential for further applications of the proposed triadic set and triadic logic. Alongside, a classical AI game-The Wumpus World-is implemented to show practical efficacy in comparison with binary implementation. Besides giving some preliminary formulations for trichotomous set theory and definition of finite automaton, development of hybrid architectures for intelligent agents and evolutionary computations are discussed as potential practical avenues for Peirce's triadic logic.

The Journal of The Textile Institute, 2015

This article describes the role of decision support systems (DSS) in agriculture, with a special emphasis to the aspects of DSS architecture and design. Based on existing research studies, an overview of factors that are crucially important for acceptance of agricultural DSS is provided. Based on these premises, a client-server agent-based architecture of DSS is presented. The server part of the solution is discussed in details with respect to the knowledge model and knowledge engine construction and integration, and demonstrated on a case study of plant-leaf recognition agent. In relationship with identified lack of relevant training data for intelligent agents, a strategy for creating a feedback link is discussed, which enables the DSS to maintain its quality over the time, and continually improve its performance.

Journal of Enterprise Information Management, 2020

Purpose-The purpose of this paper is to analyze demand forecast strategies to support a more sustainable management in a pallet supply chain, and thus avoid environmental impacts, such as reducing the consumption of forest resources. Design/methodology/approach-Since the producer presents several uncertainties regarding its demand logs, a methodology that embed zero-inflated intelligence is proposed combining fuzzy time series with clustering techniques, in order to deal with an excessive count of zeros. Findings-A comparison with other models from literature is performed. As a result, the strategy that considered at the same time the excess of zeros and low demands provided the best performance, and thus it can be considered a promising approach, particularly for sustainable supply chains where resources consumption is significant and exist a huge variation in demand over time. Originality/value-The findings of the study contribute to the knowledge of the managers and policymakers in achieving sustainable supply chain management. The results provide the important concepts regarding the sustainability of supply chain using fuzzy time series and clustering techniques.

Energies, 2023

This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY

Annals of Operations Research, 2019

Compliance monitoring for quality of web service (QoWS) has accuracy issues due to uncertain network behaviors. Existing models use precise computation-based methods for defining and monitoring QoWS requirements, but these methods have limited ability to handle uncertainties. Consequently, the accuracy of the monitoring results is degraded. Defining expected QoWS using exact values is unrealistic, as generally not all service requestors know what values should be specified in the contract. Therefore, this paper proposes an interval type-2 (IT2) fuzzy model for QoWS compliance monitoring because it has greater capability than precise computation methods to reduce the effects of uncertainties. IT2 also has greater capability than the traditional fuzzy sets to manage uncertainty problem due to its non-crisp membership degrees assigned to the input. The model is able to perform compliance monitoring on linguistically defined QoWS. The model is developed based on fuzzy C-means algorithm, and the number of clusters is optimized using a clustering validity index. The model is constructed based on a Mamdani fuzzy inference system. The results show that the IT2 model outperforms type-1 fuzzy and precise computation-based models in terms of the accuracy of monitoring results. This research results in more accurate and precise QoWS compliance monitoring. It also provides user-centric QoWS specifications because requestors can define their requirements using linguistic values. Keywords Web services monitoring • Quality of web service • QoWS monitoring • Interval type-2 fuzzy • Uncertainties

Journal of Vibration and Control, 2019

Underactuated mechanical systems are frequently encountered in several industrial and real-world applications such as robotic manipulators with elastic components, aerospace vehicles, marine vessels, and overhead container cranes. The design of accurate controllers for this kind of mechanical system can become very challenging, especially if a high level of uncertainty is involved. In this paper, an adaptive fuzzy inference system is combined with a sliding mode controller in order to enhance the control performance of uncertain underactuated mechanical systems. The proposed scheme can deal with a large class of multiple-input-multiple-output underactuated systems subject to parameter uncertainties, unmodeled dynamics, and external disturbances. The convergence properties of the resulting intelligent controller are proved by means of a Lyapunov-like stability analysis. Experimental results obtained with an overhead container crane demonstrate not only the feasibility of the proposed scheme, but also its improved efficacy for both stabilization and trajectory tracking problems.

International Journal of Primatology, 2022

Observations of early vocal behaviours in non-human primates (hereafter primates) are important for direct comparisons between human and primate vocal development. However, direct observations of births and perinatal behaviour in wild primates are rare, and the initial stages of behavioural ontogeny usually remain undocumented. Here, we report direct observations of the birth of a wild chimpanzee (Pan troglodytes schweinfurthii) in Budongo Forest, Uganda, including the behaviour of the mother and other group members. We monitored the newborn's vocal behaviour for approximately 2 hours and recorded 70 calls. We categorised the vocalisations both qualitatively, using conventional call descriptions, and quantitatively, using cluster and discriminant acoustic analyses. We found evidence for acoustically distinct vocal units, produced both in isolation and in combination, including sequences akin to adult pant hoots, a vocal utterance regarded as the most complex vocal signal produced by this species. We concluded that chimpanzees possess the capacity to produce vocal sequences composed of different call types from birth, albeit in rudimentary forms. Our observations are in line with the idea that primate vocal repertoires are largely present from birth, with fine acoustic structures undergoing ontogenetic processes. Our study provides rare and valuable empirical data on perinatal behaviours in wild primates.