William Siler, James J. Buckley

Fuzzy Expert Systems and Fuzzy Reasoning

• Gebundenes Buch

Produktbeschreibung

Hier lernen Sie, Expertensysteme auf der Basis von Fuzzy Logic zu konstruieren, die sich für den praktischen Einsatz eignen. Expertensysteme werden zunächst allgemein definiert, und die zugrundeliegende Mathematik wird eingeführt. Regelbasierte Systeme werden gründlicher besprochen als in jedem anderen Buch mit ähnlichem Thema. Am Ende jedes Kapitels können Sie Ihren Wissensstand anhand von Übungsaufgaben überprüfen. Von einem zugehörigen ftp-Server können Sie Ergänzungsmaterial abrufen. Für Praktiker und Forscher aus dem akademischen Umfeld gleichermaßen geeignet! 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.

Produktdetails

• Verlag: Wiley & Sons
• 1. Auflage
• Seitenzahl: 424
• Erscheinungstermin: 1. Dezember 2004
• Englisch
• Abmessung: 240mm x 161mm x 27mm
• Gewicht: 725g
• ISBN-13: 9780471388593
• ISBN-10: 0471388599
• Artikelnr.: 12939601

Autorenporträt

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.

Inhaltsangabe

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.