Fuzzy Expert Systems and Fuzzy Reasoning
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More About This Title Fuzzy Expert Systems and Fuzzy Reasoning
English
Coverage is accessible to practitioners and academic readers alike.
* Features end-of-chapter problems with answers provided in an appendix.
* Includes discussions of rule-based systems not available in any other book.
* Includes problem sets and tutorial programs available on the Wiley ftp site.
* Features end-of-chapter problems with answers provided in an appendix.
* Includes discussions of rule-based systems not available in any other book.
* Includes problem sets and tutorial programs available on the Wiley ftp site.
English
WILLIAM SILER, of Southern Dynamic Systems, Inc., is a former academician, having served as chairman of the Biomedical Computer Science program at SUNY Downstate Medical Center, and as professor and chairman of the Biomathematics Department at the University of Alabama at Birmingham. For the past forty years, he has been developing scientific software tools for general use. He is now Senior Scientist at the Kemp-Carraway Heart Institute at Birmingham, Alabama.
JAMES J. BUCKLEY is Associate Professor of Mathematics at the University of Alabama in Birmingham. A prominent researcher in fuzzy mathematics, he has published over 200 papers and several books on the topic.
JAMES J. BUCKLEY is Associate Professor of Mathematics at the University of Alabama in Birmingham. A prominent researcher in fuzzy mathematics, he has published over 200 papers and several books on the topic.
English
Preface.
1 Introduction.
2 Rule-Based Systems: Overview.
3 Fuzzy Logic, Fuzzy Sets, and Fuzzy Numbers: I.
4 Fuzzy Logic, Fuzzy Sets, and Fuzzy Numbers: II.
5 Combining Uncertainties.
6 Inference in an Expert System I.
7 Inference in a Fuzzy Expert System II: Modification of Data and Truth Values.
8 Resolving Contradictions: Possibility and Necessity.
9 Expert System Shells and the Integrated Development Environment (IDE).
10 Simple Example Programs.
11 Running and Debugging Fuzzy Expert Systems I: Parallel Programs.
12 Running and Debugging Expert Systems II: Sequential Rule-Firing.
13 Solving "What?" Problems when the Answer is Expressed in Words.
14 Programs that Can Learn from Experience.
15 Running On-Line in Real-Time.
Appendix.
Answers.
References.
Index.
1 Introduction.
2 Rule-Based Systems: Overview.
3 Fuzzy Logic, Fuzzy Sets, and Fuzzy Numbers: I.
4 Fuzzy Logic, Fuzzy Sets, and Fuzzy Numbers: II.
5 Combining Uncertainties.
6 Inference in an Expert System I.
7 Inference in a Fuzzy Expert System II: Modification of Data and Truth Values.
8 Resolving Contradictions: Possibility and Necessity.
9 Expert System Shells and the Integrated Development Environment (IDE).
10 Simple Example Programs.
11 Running and Debugging Fuzzy Expert Systems I: Parallel Programs.
12 Running and Debugging Expert Systems II: Sequential Rule-Firing.
13 Solving "What?" Problems when the Answer is Expressed in Words.
14 Programs that Can Learn from Experience.
15 Running On-Line in Real-Time.
Appendix.
Answers.
References.
Index.
