ABSTRACT This work reports on a study on the feasibility of applying" weighted estimator of a com... more ABSTRACT This work reports on a study on the feasibility of applying" weighted estimator of a common correlation" technique to software measurement data. This technique is a metaanalytical approach to generalizing the knowledge from individual statistical studies. The technique is applied on a data set of 100 public domain Java projects to determine if it is possible to generalize project-specific significant correlations. The results of the experiment show that the technique avoids both type I and type II errors.
Abstract—Granular Computing arose as a synthesis of insights into human-centred information proce... more Abstract—Granular Computing arose as a synthesis of insights into human-centred information processing by Zadeh in the late'90s and the Granular Computing name was coined, at this early stage, by TY Lin. Although the name is now in widespread use, or perhaps because of it, there are calls for a clarification of the distinctiveness of Granular Computing against the background of other human-centred information processing paradigms.
1 ABSTRACT Self-organising maps (SOMs) are proposed as an interactive, user-friendly tool that he... more 1 ABSTRACT Self-organising maps (SOMs) are proposed as an interactive, user-friendly tool that helps to develop a deep insight into the structure of the visually formed information granules. The rationale for this approach is founded on the following:• The unsupervised learning neural network architecture;• Visualisation of highly-dimensional data that provides basis for human interaction in delineating boundaries of information granules;
This paper presents an unsupervised hierarchical segmentation method for multi-phase images based... more This paper presents an unsupervised hierarchical segmentation method for multi-phase images based on a single level set (2-phase) method and the semi-implicit additive operator splitting (AOS) scheme which is stable, fast, and easy to implement. The method successively segments image subregions found at each step of the hierarchy using a decision criterion based on the variance of intensity across the current subregion. The segmentation continues until a specified number of levels has been reached.
Fuzzy Cognitive Maps (FCMs) were originally introduced by Kosko [11] in 1986 as an extension of c... more Fuzzy Cognitive Maps (FCMs) were originally introduced by Kosko [11] in 1986 as an extension of cognitive maps. They are a convenient modeling tool, usually categorized as a neuro-fuzzy method, for modeling and simulation of dynamic systems. One of their main advantages is an ability to incorporate and adapt human knowledge [18].
Abstract With the increased interest in application of all kinds of software systems, understandi... more Abstract With the increased interest in application of all kinds of software systems, understanding and controlling software development processes have gained increasing importance. One of the main goals, in this sense, is to build robust descriptive statistical models that would characterize them in the best possible way. However, individual experimental studies that form the basis of these models often produce different results. Consequently, the resulting models tend to differ substantially.
Relevance and consistency in rule-based systems Witold Pedrycz* and George Vukovich** *Department... more Relevance and consistency in rule-based systems Witold Pedrycz* and George Vukovich** *Department of Electrical & Computer Engineering University of Alberta, Edmonton, Canada (pedrycz@ee.ualberta.ca) and Systems Research Institute, Polish Academy of Sciences 01-447 Warsaw, Poland and **Canadian Space Agency, Spacecraft Engineering 6767 Route de l'Aéroport Saint-Hubert, Quebec J3Y 8Y9, Canada Abstract We discuss a problem of synthesis and analysis of rules based on experimental numeric data.
This study introduces new aspects of phase transition in two new hybrid intelligent systems calle... more This study introduces new aspects of phase transition in two new hybrid intelligent systems called Self-Organizing Neuro-Fuzzy Inference System (SONFIS) and Self-Organizing Rough SeT (SORST). We show how our algorithms can be taken as a linkage of government-society interaction, where government catches various states of behaviors:“solid (absolute-oppressive) or flexible (democratic)”.
Abstract Fuzzy cognitive maps (FCMs) form a convenient, simple, and powerful tool for simulation ... more Abstract Fuzzy cognitive maps (FCMs) form a convenient, simple, and powerful tool for simulation and analysis of dynamic systems. The popularity of FCMs stems from their simplicity and transparency. While being successful in a variety of application domains, FCMs are hindered by necessity of involving domain experts to develop the model. Since human experts are subjective and can handle only relatively simple networks (maps), there is an urgent need to develop methods for automated generation of FCM models.
Abstract The study is devoted to a granular analysis of data. We develop a new clustering algorit... more Abstract The study is devoted to a granular analysis of data. We develop a new clustering algorithm that organizes findings about data in the form of a collection of information granules-hyperboxes. The clustering carried out here is an example of a granulation mechanism. We discuss a compatibility measure guiding a construction (growth) of the clusters and explain a rationale behind their development.
Applications of Fuzzy Logic Technology (Proceedings Volume)
This paper presents the results of a project presently under way at Texas A&M which focuses on th... more This paper presents the results of a project presently under way at Texas A&M which focuses on the use of fuzzy logic in integrated control of manufacturing systems. The specific problems investigated here include diagnosis of critical tool wear in machining of metals via a neuro-fuzzy algorithm, as well as compensation of friction in mechanical positioning systems via an adaptive fuzzy logic algorithm.
Holmes is a tool designed to support the Sherlock [2] software product line methodology. Holmes a... more Holmes is a tool designed to support the Sherlock [2] software product line methodology. Holmes attempts to provide comprehensive support for product line development, from market and product strategy analysis to modeling, designing, and developing the resulting system.
This book presents the genuine essence of engineering of fuzzy sets. It includes sound theory, a ... more This book presents the genuine essence of engineering of fuzzy sets. It includes sound theory, a general methodological framework, efficient algorithms, and detailed validation schemes. Fuzzy Sets Engineering offers discussions in a top-down fashion, with general methodology followed by specific domains which rely strongly on the methodological foundations. Based on this methodological framework, the book then provides a careful, in-depth exposure to very diversified areas.
Abstract A digital watermarking method using image compression based on a fuzzy relational equati... more Abstract A digital watermarking method using image compression based on a fuzzy relational equation (ICF) is proposed. The method is based on least significant bit modification. If the coding system of ICF is not designed appropriately, the fuzzy relational equation will be unsolvable due to the watermarking (modification of compressed image). In order to avoid this problem, a condition for appropriate coding system design is represented in terms of the solvability degree of the fuzzy relational equation.
Abstract Fuzzy cognitive maps (FCMs) are a convenient tool for modeling of dynamic systems by mea... more Abstract Fuzzy cognitive maps (FCMs) are a convenient tool for modeling of dynamic systems by means of concepts connected by cause-effect relationships. The FCM models can be developed either manually (by the experts) or using an automated learning method (from data). Some of the methods from the latter group, including recently proposed Nonlinear Hebbian Learning (NHL) algorithm, use Hebbian law and a set of conditions imposed on output concepts.
The paper introduces an exclusion/inclusion fuzzy classification neural network. The network is b... more The paper introduces an exclusion/inclusion fuzzy classification neural network. The network is based on our GFMM [3] and it allows for two distinct types of hyperboxes to be created: inclusion hyperboxes that correspond directly to those considered in GFMM, and exclusion hyperboxes that represent contentious areas of the pattern space. The subtraction of the exclusion hyperboxes from the inclusion hyperboxes, implemented by EFC, provides for a more efficient coverage of complex topologies of data clusters.
Abstract To be fully utilized, linguistic information present in decision-making, has to be made ... more Abstract To be fully utilized, linguistic information present in decision-making, has to be made operational through information granulation. This study is concerned with information granulation present in the problems of Analytic Hierarchy Process (AHP), which is available in the characterization of a pairwise assessment of alternatives studied in the decision-making problem.
Abstract Revealing a structure in data is of paramount importance in a broad range of problems of... more Abstract Revealing a structure in data is of paramount importance in a broad range of problems of information processing. In spite of the specificity of the problem in which such analysis is realized, there is an evident commonality of all these pursuits worth emphasizing. One can distinguish between a core and a residual of the data structure. In this study, we propose a formal environment supporting these concepts and develop its algorithmic fabric.
Abstract. Presented are the investigations showing an impact of the length of data signals in har... more Abstract. Presented are the investigations showing an impact of the length of data signals in hardware implemented Kohonen Self-Organizing Maps (SOM) on the quality of the learning process. The aim of this work was to determine the allowable reduction of the number of bits in particular signals that does not deteriorate the network behavior. The efficiency of the learning process has been quantified by using the quantization error.
Abstract The dramatic increase in geospatial data occasioned by developments in digital mapping, ... more Abstract The dramatic increase in geospatial data occasioned by developments in digital mapping, remote sensing, IT, and widespread generalization of Geographic Information Systems (GIS), emphasises the importance of exploring new approaches to spatial analysis and modelling. This favours the creation of new knowledge and eventually helps the process of scientific discovery.
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Papers by Witold Pedrycz