On the Future of Data Analysis

Access Journal - Access to Science, Business, Innovation in the digital economy

Objectives: Modern production activity of railway transport of Ukraine (RTU) is characterized by high the level of complexity of processes and a wide range of conditions of uncertainty. The article is devoted to the tasks of development of unified automated intelligent analysis and control technologies indeterminate RTU processes in case of uncertainty. Methods / Approach: To achieve the goal a new model of the concept of formation of automated intellectual technologies of RTU is offered, implementation of which is based on a modular platform of unified analytical services designed for effective solution of certain typical tasks (diagnosis, classification, forecasting, management, etc.). The concept as a system includes stages of research of properties of processes, theoretical and methodological basis and methods of modeling and automated control, scenarios and intelligent acceptance procedures decisions in case of uncertainty. Results: As examples of application of the concept to the formation of unified technologies RTU presented intelligent services for diagnosing processes with several categories of uncertainty, as well as analysis and forecasting the parameters of anti-resistance processes. The analysis procedures developed in the article differ using the scheme of fuzzy control method Takagi-Sugeno adapted for diagnostic tasks with the uncertainty of different types (statistical, fuzzy, etc.), which is provided by the use integrated indicatorthe reliability index, as well as the formal capabilities of the individual accounting for the importance of controlled variables of the process model together for all rules of diagnosis, and for each rule separately. By aggregating the levels of time series of non-deterministic RTU processes developed and researched correct mathematical models and algorithms designed for unified procedures classification and research of properties of anti-persistent processes of railway transport. Conclusions: In order to develop unified intelligent automated technologies RTU developed a concept analysis and management of non-deterministic RTU processes in case of uncertainty based on the platform analytical services. In work at formation of the specified services of the automated intellectual The technology has developed advanced diagnostic procedures that use Takagi-Sugeno-type models for several categories of uncertainty, as well as methods for classifying anti-persistence processes, algorithms interpolation of levels within aggregation ranges, analysis models and short-term forecasting processes designed to develop the theoretical basis and means of improving automated systems RTU.

Journal of Risk Research

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Springer Tracts in Mechanical Engineering, 2021

This chapter describes the various approaches to analyse, quantify and evaluate uncertainty along the phases of the product life cycle. It is based on the previous chapters that introduce a consistent classification of uncertainty and a holistic approach to master the uncertainty of technical systems in mechanical engineering. Here, the following topics are presented: the identification of uncertainty by modelling technical processes, the detection and handling of data-induced conflicts, the analysis, quantification and evaluation of model uncertainty as well as the representation and visualisation of uncertainty. The different approaches are discussed and demonstrated on exemplary technical systems.

Data analysis as an area of importance has grown exponentially, especially during the past couple of decades. This can be attributed to a rapidly growing computer industry and the wide applicability of computational techniques, in conjunction with new advances of analytic tools. This being the case, the need for literature that addresses this is self-evident. New publications appear as printed or e-books covering the need for information from all fields of science and engineering thanks to the wide applicability of data analysis and statistic packages. The book is a collective work by a number of leading scientists, analysts, engineers, mathematicians and statisticians who have been working on the front end of data analysis. The chapters included in this collective volume represent a cross-section of current concerns and research interests in the above-mentioned scientific areas. This volume is divided into three parts with a total of 16 chapters in a form to provide the reader with both theoretical and applied information on data analysis methods, models and techniques along with appropriate applications. Part 1 focuses on Financial Data Analysis and Methods and contains four chapters on "Forecasting Methods in Extreme Scenarios and Advanced Data Analytics for Improved Risk Estimation" by George-Jason Siouris, xiv Data Analysis and Applications 4

Mechanical Systems and Signal Processing, 2013

The present paper is about data corrupted by both aleatoric and epistemic uncertainty. A unification of randomness, which represents aleatoric uncertainty, and fuzziness, which represents epistemic uncertainty, is dicussed in detail. As a result, the main uncertainty characteristics, i.e., variability, incompleteness and imprecision, can be described. With a focus on engineering problems the aim is to bridge the imprecision of data to the decision making process. Suitable fields of applications are highlighted; remarks on the numerical treatment are given.