Muutke küpsiste eelistusi

E-raamat: Fuzzy Logic with Engineering Applications 3rd Revised edition [Wiley Online]

  • Formaat: 606 pages, Illustrations
  • Ilmumisaeg: 15-Mar-2010
  • Kirjastus: Wiley-Blackwell
  • ISBN-10: 1119994373
  • ISBN-13: 9781119994374
Teised raamatud teemal:
  • Wiley Online
  • Hind: 91,19 €*
  • * hind, mis tagab piiramatu üheaegsete kasutajate arvuga ligipääsu piiramatuks ajaks
  • Formaat: 606 pages, Illustrations
  • Ilmumisaeg: 15-Mar-2010
  • Kirjastus: Wiley-Blackwell
  • ISBN-10: 1119994373
  • ISBN-13: 9781119994374
Teised raamatud teemal:
The first edition of Fuzzy Logic with Engineering Applications (1995) was the first classroom text for undergraduates in the field. Now updated for the second time, this new edition features the latest advances in the field including material on expansion of the MLFE method using genetic algorithms, cognitive mapping, fuzzy agent-based models and total uncertainty. Redundant or obsolete topics have been removed, resulting in a more concise yet inclusive text that will ensure the book retains its broad appeal at the forefront of the literature. Fuzzy Logic with Engineering Applications, 3rd Edition is oriented mainly towards methods and techniques. Every chapter has been revised, featuring new illustrations and examples throughout. Supporting MATLAB code is downloadable at www.wileyeurope.com/go/fuzzylogic. This will benefit student learning in all basic operations, the generation of membership functions, and the specialized applications in the latter chapters of the book, providing an invaluable tool for students as well as for self-study by practicing engineers.
About the Author xiii
Preface to the Third Edition xv
Introduction
1(24)
The Case for Imprecision
2(1)
A Historical Perspective
3(3)
The utility of Fuzzy Systems
6(2)
Limitations of Fuzzy Systems
8(2)
The Illusion: Ignoring Uncertainty and Accuracy
10(3)
Uncertainty and Information
13(1)
The Unknown
14(1)
Fuzzy Sets and Membership
14(2)
Chance Versus Fuzziness
16(2)
Sets as Points in Hypercubes
18(2)
Summary
20(1)
References
20(1)
Problems
21(4)
Classical Sets and Fuzzy Sets
25(23)
Classical Sets
26(8)
Operations on Classical Sets
28(1)
Properties of Classical (Crisp) Sets
29(3)
Mapping of Classical Sets to Functions
32(2)
Fuzzy Sets
34(7)
Fuzzy Set Operations
35(2)
Properties of Fuzzy Sets
37(3)
Alternative Fuzzy Set Operations
40(1)
Summary
41(1)
References
42(1)
Problems
42(6)
Classical Relations and Fuzzy Relations
48(41)
Cartesian Product
49(1)
Crisp Relations
49(5)
Cardinalityof Crisp Relations
51(1)
Operation on Crisp Relations
52(1)
Properties of Crisp Relations
52(1)
Composition
53(1)
Fuzzy Relations
54(8)
Cardinality of Fuzzy Relations
55(1)
Operations on Fuzzy Relations
55(1)
Properties of Fuzzy Relations
55(1)
Fuzzy Cartesian Product and Composition
55(7)
Tolerance and Equivalence Relations
62(3)
Crisp Equivalence Relation
63(1)
Crisp Tolerance Relation
64(1)
Fuzzy Tolerance and Equivalence Relations
65(3)
Value Assignments
68(4)
Cosine Amplitude
69(2)
Max-Min Method
71(1)
Other Similarity Methods
71(1)
Other Forms of the Composition Operation
72(1)
Summary
72(1)
References
73(1)
Problems
73(16)
Properties of Membership Functions, Fuzzification, and Defuzzification
89(28)
Features of the Membership Function
90(2)
Various Forms
92(1)
Fuzzification
93(2)
Defuzzification to Crisp Sets
95(2)
λ Cuts for Fuzzy Relations
97(1)
Defuzzification to Scalars
98(12)
Summary
110(1)
References
111(1)
Problems
112(5)
Logic and Fuzzy Systems
117(57)
Logic
117(22)
Classical Logic
118(6)
Proof
124(7)
Fuzzy Logic
131(3)
Approximate Reasoning
134(4)
Other Forms of the Implication Operation
138(1)
Fuzzy Systems
139(20)
Natural Language
140(2)
Linguistic Hedges
142(3)
Fuzzy (Rule-Based) Systems
145(3)
Graphical Techniques of Inference
148(11)
Summary
159(2)
References
161(1)
Problems
162(12)
Development of Membership Functions
174(37)
Membership Value Assignments
175(31)
Intuition
175(1)
Inference
176(2)
Rank Ordering
178(1)
Neural Networks
179(10)
Genetic Algorithms
189(10)
Inductive Reasoning
199(7)
Summary
206(1)
References
206(1)
Problems
207(4)
Automated Methods for Fuzzy Systems
211(34)
Definitions
212(3)
Batch Least Squares Algorithm
215(4)
Recursive Least Squares Algorithm
219(3)
Gradient Method
222(5)
Clustering Method
227(2)
Learning From Examples
229(4)
Modified Learning From Examples
233(9)
Summary
242(1)
References
242(1)
Problems
243(2)
Fuzzy Systems Simulation
245(31)
Fuzzy Relational Equations
250(1)
Nonlinear Simulation Using Fuzzy Systems
251(4)
Fuzzy Associative Memories (FAMS)
255(9)
Summary
264(1)
References
265(1)
Problems
266(10)
Decision Making with Fuzzy Information
276(56)
Fuzzy Synthetic Evaluation
278(2)
Fuzzy Ordering
280(3)
Nontransitive Ranking
283(2)
Preference and Consensus
285(4)
Multiobjective Decision Making
289(5)
Fuzzy Bayesian Decision Method
294(10)
Decision Making Under Fuzzy States and Fuzzy Actions
304(13)
Summary
317(1)
References
318(1)
Problems
319(13)
Fuzzy Classification
332(37)
Classification by Equivalence Relations
333(6)
Crisp Relations
333(2)
Fuzzy Relations
335(4)
Cluster Analysis
339(1)
Cluster Validity
340(1)
c-Means Clustering
340(1)
Hard c-Means (HCM)
341(8)
Fuzzy c-Means (FCM)
349(8)
Fuzzy c-Means Algorithm
352(5)
Classification Metric
357(3)
Hardening the Fuzzy c-Partition
360(1)
Similarity Relations from Clustering
361(1)
Summary
362(1)
References
362(1)
Problems
363(6)
Fuzzy Pattern Recognition
369(39)
Feature Analysis
370(1)
Partitions of the Feature Space
371(1)
Single-Sample Identification
371(7)
Multifeature Pattern Recognition
378(12)
Image Processing
390(8)
Summary
398(1)
References
399(1)
Problems
400(8)
Fuzzy Arithmetic and the Extension Principle
408(29)
Extension Principle
408(10)
Crisp Functions, Mapping, and Relations
409(2)
Functions of Fuzzy Sets-Extension Principle
411(1)
Fuzzy Transform (Mapping)
411(2)
Practical Considerations
413(5)
Fuzzy Arithmetic
418(2)
Interval Analysis in Arithmetic
420(2)
Approximate Methods of Extension
422(10)
Vertex Method
423(3)
DSW Algorithm
426(2)
Restricted DSW Algorithm
428(1)
Comparisons
429(3)
Summary
432(1)
References
433(1)
Problems
433(4)
Fuzzy Control Systems
437(64)
Control System Design Problem
439(3)
Control (Decision) Surface
440(1)
Assumptions in a Fuzzy control System Design
441(1)
Simple Fuzzy Logic Controllers
441(1)
Examples of Fuzzy Control System Design
442(11)
Aircraft Landing Control Problem
446(7)
Fuzzy Engineering Process Control
453(11)
Classical Feedback Control
453(4)
Fuzzy Control
457(7)
Fuzy Statistical Process Control
464(14)
Measurement Data - Traditional SPC
466(6)
Attribute Data-Traditional SPC
472(6)
Industrial Applications
478(1)
Summary
479(3)
References
482(2)
Problems
484(17)
Miscellaneous Topics
501(29)
Fuzzy Optimization
501(7)
One-Dimensional Optimization
502(6)
Fuzzy Cognitive Mapping
508(12)
Concept Variables and Causal Relations
508(2)
Fuzzy Cognitive Maps
510(10)
Agent-Based Models
520(4)
Summary
524(1)
References
525(1)
Problems
526(4)
Monotone Measures: Belief, Plausibility, Probability, and Possibility
530(49)
Monotone Measures
531(1)
Belief and Plausibility
532(5)
Evidence Theory
537(3)
Probability Measures
540(2)
Possibility and Necessity Measures
542(7)
Possibility Distributions as Fuzzy Sets
549(2)
Possibility Distributions Derived from Empirical Intervals
551(18)
Deriving Possibility Distributions from Overlapping Intervals
552(2)
Redistributing Weight from Nonconsonant to Consonant Intervals
554(14)
Comparision of Possibility Theory and Probability Theory
568(1)
Summary
569(2)
References
571(1)
Problems
572(7)
Index 579
Professor Timothy J. Ross is a registered professional engineer with over 30 years experience in the fields of computational mechanics, hazard survivability, structural dynamics, structural safety, stochastic processes, risk assessment, and fuzzy systems. He has been an engineering educator at the University of New Mexico (UNM) since 1987 and is the founding Editor-in-Chief of the International Journal of Intelligent and Fuzzy Systems.