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E-raamat: Introduction to Fuzzy Logic and Fuzzy Sets

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This book is intended to be an undergraduate introduction to the theory of fuzzy sets. We envision, sometime in the future, a curriculum in fuzzy sys­ tems theory, which could be in computer /information sciences, mathematics, engineering or economics (business, finance), with this book as the starting point. It is not a book for researchers but a book for beginners where you learn the basics. This course would be analogous to a pre-calculus course where a student studies algebra, functions and trigonometry in preparation for more advanced courses. Chapters 3 through 11 are on fuzzy algebra, fuzzy functions, fuzzy trigonometry, fuzzy geometry, and solving fuzzy equations. However, after this course the student doesn't go on to calculus but to more specialized courses in fuzzy systems theory like fuzzy clustering, fuzzy pattern recogni­ tion, fuzzy database, fuzzy image processing and computer vision, robotics, intelligent agents, soft computing, fuzzy rule based systems (control, expert systems), fuzzy decision making, applications to operations research, fuzzy mathematics, fuzzy systems modeling, etc. Therefore, very little of most of these topics are included in this book. There are many new topics included in this book. Let us point out some of them here: (1) mixed fuzzy logic (Section 3.5); (2) three methods of solving fuzzy equation/problems (Chapter 5); (3) solving fuzzy inequalities (Chapter 6); (4) inverse fuzzy functions (Section 8.5); (5) fuzzy plane geometry (Chap­ ter 9); (6) fuzzy trigonometry (Chapter 10); and (7) fuzzy optimization based on genetic algorithms (Chapter 16).

Arvustused

From the reviews:









"A well written book which enables to the reader fundamental orientation in the fuzzy logic. From the educational point of view the book is very well organized. Majority of chapters begin with several motivation examples and at the end of each chapter there are a lot of solved and unsolved examples. dedicated to undergraduate students as a textbook. it may be suitable for readers from the application sphere who are not professionals in fuzzy logic but utilize some fuzzy methods ." (Petr Vysoky, Neural Network World, Vol. 13 (4), 2003)



"The book is an undergraduate textbook covering as an impressively broad range of topics . The book is well-written each of the chapters providing basic definitions, examples, and exercises. The book is intended as an introductory textbook on the theory of fuzzy sets, functioning as the basis for a curriculum in fuzzy systems. I would recommend the book to the reader who wants to get an introductory overview of how much of mathematics can be fuzzified." (Marc Pauly, Expert Update, Vol. 5 (2), 2002)



"This book is an undergraduate introduction to the theory of fuzzy sets, giving basic information for beginners. Each chapter ends with a set of relevant problems and exercises. The book can be recommended as a good textbook for students and beginners in computer science, engineering or economics interested in non-probabilistic uncertainty modeling." (R. Mesiar, Zentralblatt MATH, Vol. 985, 2002)

Muu info

Springer Book Archives
Introduction
1(4)
Logic
5(16)
Introduction
5(1)
Propositional Logic
5(7)
Exercises
10(2)
Crisp Sets
12(5)
Exercises
15(2)
Fuzzy Logic
17(4)
Exercises
19(2)
Fuzzy Sets
21(34)
Introduction
21(1)
Fuzzy Sets
21(10)
Exercises
29(2)
t-norms, t-conorms
31(7)
Exercises
36(2)
Algebra of Fuzzy Sets
38(4)
Exercises
40(2)
Mixed Fuzzy Logic
42(4)
Exercises
44(2)
Alpha-Cuts
46(4)
Exercises
48(2)
Distance Between Fuzzy Sets
50(5)
Exercises
52(3)
Fuzzy Numbers
55(40)
Introduction
55(1)
Fuzzy Numbers
55(8)
Exercises
60(3)
Fuzzy Arithmetic
63(16)
Extension Principle
63(3)
Exercises
66(2)
Interval Arithmetic
68(1)
Exercises
69(2)
Alfa-Cuts and Interval Arithmetic
71(3)
Exercises
74(2)
Properties of Fuzzy Arithmetic
76(2)
Exercises
78(1)
Fuzzy Max and Min
79(5)
Exercises
82(2)
Inequalities
84(7)
Exercises
89(2)
Defuzzification
91(4)
Exercises
93(2)
Fuzzy Equations
95(14)
Introduction
95(1)
Linear Equations
95(7)
Classical Solution
96(1)
Extension Principle Solution
97(2)
Alfa-Cut and Interval Arithmetic Solution
99(2)
Exercises
101(1)
Other Fuzzy Equations
102(7)
Exercises
106(3)
Fuzzy Inequalities
109(6)
Introduction
109(1)
Solving A · X + B ≤ C
109(3)
A · X2 + B · X + C ≥ D (or ≥ D)
112(3)
Exercises
114(1)
Fuzzy Relations
115(26)
Introduction
115(1)
Definitions
115(7)
Exercises
120(2)
Transitive Closure
122(7)
Exercises
126(3)
Fuzzy Equivalence Relation
129(5)
Exercises
132(2)
Fuzzy Relation Equations
134(7)
Exercises
138(3)
Fuzzy Functions
141(34)
Introduction
141(1)
Extension Principle
141(9)
Exercises
147(3)
Alpha-Cuts and Interval Arithmetic
150(5)
Exercises
153(2)
Types of Fuzzy Functions
155(8)
Exercises
161(2)
Inverse Functions
163(5)
Exercises
166(2)
Derivatives
168(7)
Exercises
173(2)
Fuzzy Plane Geometry
175(10)
Exercises
181(4)
Fuzzy Trigonometry
185(10)
Introduction
185(1)
Standard Fuzzy Trigonometry
185(7)
Exercises
190(2)
Hyperbolic Trigonometric Functions
192(3)
Exercises
194(1)
Systems of Fuzzy Linear Equations
195(8)
Exercises
201(2)
Possibility Theory
203(12)
Introduction
203(1)
Discrete Possibilities
203(5)
Exercises
206(2)
Fuzzy Markov Chains
208(7)
Exercises
212(3)
Neural Nets
215(16)
Introduction
215(1)
Layered, Feedforward, Neural Nets
215(9)
Exercises
222(2)
Fuzzy Neural Nets
224(7)
Exercises
229(2)
Approximate Reasoning
231(22)
Introduction
231(1)
Approximate Reasoning
231(9)
Exercises
237(3)
Multiple Rules
240(4)
Exercises
242(2)
Discrete Case
244(5)
Exercises
248(1)
Other Methods
249(4)
Exercises
252(1)
Genetic Algorithms
253(8)
Exercises
259(2)
Fuzzy Optimization
261(16)
Introduction
261(1)
Maximum / Minimum of Fuzzy Functions
261(7)
Exercises
266(2)
Fuzzy Problems
268(9)
Exercises
274(3)
Index 277(6)
List of Figures 283(2)
List of Tables 285