.

0 (hodnocen0 x )

(1.5) Půjčeno:3x 

BK

Bristol ; Philadelphia : Adam Hilger, c1989

248 s. ; 24 cm

ISBN 0-85274-583-4 (váz.)

čeština

Obsahuje bibliografii na s. 236-243 a rejstřík

000241889

INTRODUCTION // PART I Theory // 1. SURVEY OF THE FUNDAMENTAL NOTIONS // 1.1 Sets and basic operations // 1.1.1 Classes and sets // 1.1.2 Basic operations // 1.2 Relations and structures // 1.2.1 Relations and functions // 1.2.2 Structures // First-order logic // Formal languages // 2. FUZZY SET THEORY // 2.1 Reasoning on the notion of a fuzzy set // 2.2 The notion of a fuzzy set // 2.2.1 Definition of a fuzzy set // 2.2.2 The lattice of membership grades // 2.2.3 Representation theorem and cardinality of fuzzy sets // Operations on fuzzy sets // 2.3.1 Basic operations // 2.3.2 Other important notions and their properties // 2.3.3 Extension principle // 2.3.4 Operations on fuzzy sets of type 2 // 2.3.5 Measures of fuzziness // 2.4 Fuzzy structures // 2.4.1 Fuzzy relations and structures // 2.4.1(a) Fuzzy relations and functions // 2.4.1(b) Fuzzy relation equations // 2.4.1(c) Fuzzy functions // 2.4.2 Similarity relations // 2.4.3 Special fuzzy structures // 2.4.3(a) Fuzzy ordering // 2.4.3(b) Fuzzy groups // 2.4.3(c) Fuzzy topology // 2.4.3(d) Probability of fuzzy events // 2.5 Fuzzy numbers // 2.5.1 Basic properties of fuzzy numbers // 2.5.2 Basic operations on fuzzy numbers // 2.5.3 Ordering of fuzzy numbers // 3. THE MODEL OF NATURAL LANGUAGE SEMANTICS AND LINGUISTIC VARIABLES // 3.1 The model of natural language semantics // 3.1.1 The semantics of words // 3.1.2 The semantics of expressions // 3.1.3 Linguistic modifiers // Linguistic variables // The linguistic approximation // 4. LUZZY LOGIC // 4.1 Many-valued first-order fuzzy logic // 4.1.1 Introduction // 4.1.2 Truth values and generalised functions // 4.1.3 Syntax and semantics of first-order fuzzy logic // 4.1.4 Luzzy theories of the first order // 4.1.5 Completeness theorems // 4.2 Linguistic logic // 4.2.1 Linguistic truth values // 4.2.2 Expressing linguistic truth values // Approximate reasoning //

PART II Applications // 5. DECISION AND CONTROL // 5.1 Decision // 5.1.1 Decision in a fuzzy environment // 5.1.2 Determination of weights // 5.1.3 Decision based on aggregation of preferences // 5.1.4 Decision based on a linguistically expressed contribution of alternatives // 5.2 Control // 5.2.1 The fuzzy controller // 5.2.2 Examples of fuzzy controllers 171 // 5.3 Presentation of information 174 // 5.3.1 Reduction of information 174 // 5.3.2 Toleration search of misspelled words 174 // 6. FUZZY SYSTEMS 181 // 6.1 Dynamic fuzzy systems 181 // 6.2 General fuzzy models, examples and methodology . 186 // 6.2.1 General fuzzy models 186 // 6.2.2 Some examples of fuzzy models 189 // 6.2.3 Methodology of fuzzy model construction . 192 // 6.3 Evaluation of system behaviour 193 // 6.4 Preference of system parameters 196 // 6.5 Fuzzy automata 201 // 7. FUZZY ALGORITHMS AND PROGRAMMING // LANGUAGES 205 // 7.1 Fuzzy algorithms 205 // 7.1.1 The concept of the fuzzy algorithm 207 // 7.1.2 Interpretation and execution of fuzzy // instructions 211 // 7.2 Linguistically oriented programming languages 211 // 7.2.1 Introduction 211 // 7.2.2 The programming language L.P.L 211 // 7.2.3 The possible applications of linguistically // oriented programming languages 214 // 8. OTHER APPLICATIONS 216 // 8.1 Linear programming 216 // 8.2 Cluster analysis and pattern recognition 217 // 8.3 Situation analysis in power system working 218 // 8.4 Database systems 219 // 8.5 Psychology 220 // 8.6 Applications in other fields 221 // 9. GENERAL PROBLEMS OF FUZZY SET THEORY 222 // 9.1 Determination of the membership function 222 // 9.2 Theoretical problems with the foundations of fuzzy // set theory 226 // 9.2.1 Vagueness and indiscernibility 226 // 9.2.2 Alternative set theory . 227 // 9.2.3 Fuzzy equality and nebulae 229 // 9 // 9.2.4 Axiomatisation of fuzzy sets 231 // 9.2.5 Discussion 232 // 9.3. Historical remarks 233 // References 236 // Index 245