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Fuzzy Sets, Decision Making, and Expert Systems
In the two decades since its inception by L. Zadeh, the theory of fuzzy sets has matured into a wide-ranging collection of concepts, models, and tech niques for dealing with complex phenomena which do not lend themselves to analysis by classical methods based on probability theory and bivalent logic. Nevertheless, a question which is frequently raised by the skeptics is: Are there, in fact, any significant problem areas in which the use of the theory of fuzzy sets leads to results which could not be obtained by classical methods? The approximately 5000 publications in this area, which are scattered over many areas such as artificial intelligence, computer science, control engineering, decisi...
Fuzzy Set Theory — and Its Applications
Since its inception 20 years ago the theory of fuzzy sets has advanced in a variety of ways and in many disciplines. Applications of this theory can be found in artificial intelligence, computer science, control engineering, decision theory, expert systems, logic, management science, operations research, pattern recognition, robotics and others. Theoretical advances, too, have been made in many directions, and a gap has arisen between advanced theoretical topics and applications, which often use the theory at a rather elementary level. The primary goal of this book is to close this gap - to provide a textbook for courses in fuzzy set theory and a book that can be used as an introduction. This revised book updates the research agenda, with the chapters of possibility theory, fuzzy logic and approximate reasoning, expert systems and control, decision making and fuzzy set models in operations research being restructured and rewritten. Exercises have been added to almost all chapters and a teacher's manual is available upon request.
Fuzzy Reasoning in Decision Making and Optimization
Many decision-making tasks are too complex to be understood quantitatively, however, humans succeed by using knowledge that is imprecise rather than precise. Fuzzy logic resembles human reasoning in its use of imprecise informa tion to generate decisions. Unlike classical logic which requires a deep under standing of a system, exact equations, and precise numeric values, fuzzy logic incorporates an alternative way of thinking, which allows modeling complex systems using a higher level of abstraction originating from our knowledge and experience. Fuzzy logic allows expressing this knowledge with subjective concepts such as very big and a long time which are mapped into exact numeric ranges. S...
Fuzzy Sets Theory and Applications
Problems in decision making and in other areas such as pattern recogni tion, control, structural engineering etc. involve numerous aspects of uncertainty. Additional vagueness is introduced as models become more complex but not necessarily more meaningful by the added details. During the last two decades one has become more and more aware of the fact that not all this uncertainty is of stochastic (random) cha racter and that, therefore, it can not be modelled appropriately by probability theory. This becomes the more obvious the more we want to represent formally human knowledge. As far as uncertain data are concerned, we have neither instru ments nor reasoning at our disposal as well define...
Introduction to Neuro-Fuzzy Systems
Fuzzy sets were introduced by Zadeh (1965) as a means of representing and manipulating data that was not precise, but rather fuzzy. Fuzzy logic pro vides an inference morphology that enables approximate human reasoning capabilities to be applied to knowledge-based systems. The theory of fuzzy logic provides a mathematical strength to capture the uncertainties associ ated with human cognitive processes, such as thinking and reasoning. The conventional approaches to knowledge representation lack the means for rep resentating the meaning of fuzzy concepts. As a consequence, the approaches based on first order logic and classical probablity theory do not provide an appropriate conceptual framewo...
Hepatotoxicity
Written by the foremost authority in the field, this volume is a comprehensive review of the multifaceted phenomenon of hepatotoxicity. Dr. Zimmerman examines the interface between chemicals and the liver; the latest research in experimental hepatotoxicology; the hepatotoxic risks of household, industrial, and environmental chemicals; and the adverse effects of drugs on the liver. This thoroughly revised, updated Second Edition features a greatly expanded section on the wide variety of drugs that can cause liver injury. For quick reference, an appendix lists these medications and their associated hepatic injuries. Also included are in-depth discussions of drug metabolism and factors affecting susceptibility to liver injury.
Motivation and Self-Regulated Learning
This volume focuses on the role of motivational processes – such as goals, attributions, self-efficacy, outcome expectations, self-concept, self-esteem, social comparisons, emotions, values, and self-evaluations– in self-regulated learning. It provides theoretical and empirical evidence demonstrating the role of motivation in self-regulated learning, and discusses detailed applications of the principles of motivation and self-regulation in educational contexts. Each chapter includes a description of the motivational variables, the theoretical rationale for their importance, research evidence to support their role in self-regulation, suggestions for ways to incorporate motivational variables into learning contexts to foster self-regulatory skill development, and achievement outcomes.
Applied General Systems Research
This volume consists of a selection of papers presented at the International Conference on Applied General Systems Research: Recent Developments and Trends which was held on the campus of the State University of New York at Binghamton in August 15-19, 1977, under the sponsorship of the Special Panel on Systems Science of the NATO Scientific Affairs Division. General systems research is a fairly new field which has been developing in the course of the last two or three decades. In my op~n10n, it can be best described as a movement which involves the study of all structural and context independent aspects of problem solving. As such, it is cross-disciplinary in nature and, in this sense, it mi...
