Terano T., Asai K., Sugeno M. Fuzzy systems theory and its applications

San Diego, CA : Academic Press, 1992. — xii, 268 p. — ISBN: 0-12-685245-6.Fuzzy sets were first advocated by Professor L. A. Zadeh in 1965. Besides a few specialists, the world didn't pay much attention to fuzzy sets for the first 10 years, but recently there has been a rapid growth in the number of researchers and papers devoted to them. The field has developed so far as to establish the International Fuzzy Systems Association (IFSA).
On the other hand, it is said that three conditions are necessary for the establishment of a new field: first, a societal need; second, a new methodology (both ideas and techniques); and third, attractiveness to researchers. Let's see how well fuzzy set theory fulfills these conditions.
Several books explaining fuzzy sets have already been published. However, most of them have centered on theoretical explanations, and it has been difficult for those who want to learn about fuzzy theory for practical purposes to become familiar with it Those who want to make use of fuzzy sets as a tool are more interested in its characteristics, problems, comparisons with other methodologies, rules of operations, and hardware than in strict theory.. In consideration of these needs, this book was planned to be a reference book for those aiming at practical use. In contrast to theory, research into practical uses has no framework Since the practical applications of fuzzy theory extend to a wide variety of fields, the processes of analysis, interpretation, and establishment of mathematical models are different for each problem. In other words, each one is an independent creation. Therefore, this book takes the form of a collection of examples, and theory is used only to the extent needed to explain the situations. We hope that the readers of this book understand the motivations of the researchers, the circumstances of the problems, and the features of fuzzy set theory through these case studies and are able to apply them in their own work.
Happily, Japan is in the first rank when it comes to practical applications of fuzzy sets, and there is no lack of examples. This book may prove an opportunity to provide a stimulus to the societal needs for fuzzy sets, and thus research will grow wider and deeper.The How, What, and Why of Conversion to Fuzzy Systems.
The Concept of Fuzzy Theory.
Applications Now and the Future Outlook.
THE BASICS OF FUZZY THEORY.
Quantification of Ambiguity.
Fuzzy Sets.
Crisp Sets.
Operations with Fuzzy Sets.
Cuts and the Extension Principle.
Operations with Fuzzy Numbers.
Fuzzy Propositions.
FUZZY RELATIONS.
Fuzzy Relations.
Operations for Fuzzy Relations.
Basic Properties of Fuzzy Relations.
Fuzzy Relations and Fuzzy Reasoning.
Fuzzy Relational Equations.
Various Types of Fuzzy Relations.
Similarity Relations and Fuzzy Order Relations.
FUZZY REGRESSION MODELS.
Linear Possibility Systems.
Linear Possibility Regression Model.
Examples of Applications.STATISTICAL DECISION MAKING.
Fuzzy Probability and Fuzzy Entropy.
Fuzzy-Bayes Decision Making.
Fuzzy Discrimination Methods.
FUZZY QUANTIFICATION THEORY.
Characteristics of Fuzzy Quantification Theory.
Fuzzy Quantification Theory I.
Fuzzy Quantification Theory II.
Fuzzy Quantification Theory III.
Fuzzy Quantification Theory IV.
A Note on Applications Notes.
FUZZY MATHEMATICAL PROGRAMMING.
Basic Concept and General Formulation.
Fuzzy Linear Programming.EVALUATION.
Fuzzy Measure.
Fuzzy Integrals.
DIAGNOSIS.
Ambiguity in Diagnosis.
Diagnosis Using Fuzzy Relations.
Diagnosis Using Symptom Patterns and Degrees of Conformity.
Applications of Knowledge Engineering in Diagnosis.
CONTROL.
The Form of Fuzzy Control Rules and Inference Methods.
Planning of Fuzzy Controllers.
Features of Fuzzy Control.
HUMAN ACTIVITIES.
Human Reliability Models.
Data Entry Systems.
Multistage Decision Making Using Fuzzy Dynamic Programming.
ROBOTS.
Path-Judging Robot.
Object-Grasping Robot.
Placement Inference Robot.
IMAGE RECOGNITION.
Shape Recognition and Distance/Direction Information: Extraction Using a CCD Camera.
Texture Analysis of Aerial Photographs.
DATABASES.
Standard Databases.
Fuzzy Databases.
INFORMATION RETRIEVAL.
Information Retrieval and Modeling of Estimation Processes Using Fuzzification Functions.
Prototype Document Retrieval System 239.
Characteristics of Request Concepts and Recognition Efficiency.
The Role of A Priori Knowledge and Intelligent Interfaces.
EXPERT SYSTEM FOR DAMAGE ASSESSMENT.
Expert Systems and Fuzzy Knowledge.
Expression of Problems that Contain Uncertainty.
Dempster — Shafer Theory and Its Extension to Fuzzy Sets.
SPERIL System.