Fuzzy Logic and Expert Systems Applications

0-12-443866-0

Table of contents :
Front Cover……Page 1
Fuzzy Logic and Expert Systems Applications……Page 4
Copyright Page……Page 5
Contents……Page 6
Contributors……Page 14
Preface……Page 16
I. Introduction……Page 22
II. Fuzzy Classification and Fuzzy Modeling by Nonfuzzy Neural Networks……Page 27
III. Interval-Arithmetic-Based Neural Networks……Page 48
IV. Fuzzified Neural Networks……Page 61
V. Conclusion……Page 72
References……Page 73
I. Introduction……Page 78
II. Structure of Fuzzy Systems for Modeling and Control……Page 81
III. Design 1: A Fuzzy Neural Network with an Additional OR Layer……Page 97
IV. Design 2: A Fuzzy Neural Network Based on Hierarchical Space Partitioning……Page 115
V. Conclusion……Page 138
Appendix……Page 139
References……Page 141
I. Introduction……Page 144
II. Nonlinear Thresholded Artificial Neurons……Page 145
III. Production Rules……Page 146
IV. Forward Chaining……Page 148
V. Chunking……Page 153
VI. Neural Tools for Uncertain Reasoning: Toward Hybrid Extensions……Page 161
VII. Qualitative and Quantitative Uncertain Reasoning……Page 166
VIII. Purely Neural, Rule-Based Diagnostic System……Page 179
IX. Conclusions……Page 192
References……Page 194
I. Introduction……Page 196
II. Representation of a Neuron……Page 197
III. Converting Neural Networks to Boolean Functions……Page 200
IV. Example Application of Boolean Rule Extraction……Page 206
V. Network Design, Pruning, and Weight Decay……Page 208
VI. Simplifying the Derived Rule Base……Page 213
VII. Example of the Construction of a Rule-Based Intelligent System……Page 218
VIII. Using Rule Extraction to Verify the Networks……Page 223
IX. Conclusions……Page 229
References……Page 230
I. Introduction……Page 232
II. Expert Systems: Some Problems and Relevance of Soft Computing……Page 235
III. Connectionist Expert Systems: A Review……Page 246
IV. Neuro-Fuzzy Expert Systems……Page 248
V. Other Hybrid Models……Page 255
References……Page 258
I. Introduction……Page 264
II. Fuzzy Reasoning Schemes……Page 266
III. Design of the Conclusion Part in Functional Reasoning……Page 269
IV. Fuzzy Gaussian Neural Networks……Page 270
V. Attitude Control Application Example……Page 279
VI. Mobile Robot Example……Page 291
VII. Conclusions……Page 302
References……Page 303
I. Introduction……Page 306
II. Fuzzy Neural Network……Page 307
III. Mapping Capability of the Fuzzy Neural Network……Page 320
IV. Model Reference Control System Using a Fuzzy Neural Network……Page 326
V. Simulation Results……Page 330
References……Page 333
I. Introduction, Motivations, Basic Problems……Page 336
II “Classical” Methods of Nonlinear System Identification……Page 348
III. Wavelets: What They Are, and Their Use in Approximating Functions……Page 365
IV. Wavelets: Their Use in Nonparametric Estimation……Page 377
V. Wavelet Network for Practical System Identification……Page 384
VI. Fuzzy Models: Expressing Prior Knowledge in Nonlinear Nonparametric Models……Page 391
VII. Experimental Results……Page 400
VIII. Discussion and Conclusions……Page 418
IX. Appendix: Three Methods for Regressor Selection……Page 421
References……Page 430
Index……Page 434