Fuzzy Expert Systems
โ Scribed by Abraham Kandel
- Book ID
- 127435106
- Publisher
- CRC Press
- Year
- 1991
- Tongue
- English
- Weight
- 7 MB
- Edition
- 1
- Category
- Library
- ISBN
- 084934297X
No coin nor oath required. For personal study only.
โฆ Synopsis
Until recently, fuzzy logic was the intellectual plaything of a handful of researchers. Now it is being used to enhance the power of intelligent systems, as well as improve the performance and reduce the cost of intelligent and "smart" products appearing in the commercial market. Fuzzy Expert Systems focuses primarily on the theory of fuzzy expert systems and their applications in science and engineering. In doing so, it provides the first comprehensive study of "soft" expert systems and applications for those systems. Topics covered include general purpose fuzzy expert systems, processing imperfect information using structured frameworks, the fuzzy linguistic inference network generator, fuzzy associative memories, the role of approximate reasoning in medical expert systems, MILORD (a fuzzy expert systems shell), and COMAX (an autonomous fuzzy expert system for tactical communications networks.Fuzzy Expert Systems provides an invaluable reference resource for researchers and students in artificial intelligence (AI) and approximate reasoning (AR), as well as for other researchers looking for methods to apply similar tools in their own designs of intelligent systems.
๐ SIMILAR VOLUMES
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.
Fuzzy sets were for a long time not accepted by the AI community. Now they have become highly evolved and their techniques are well established.ย This book will teach the reader how to construct a fuzzy expert system to solve real-world problems. After a general discussion of expert systems, the bas
We describe a fuzzy rule based expert production system. The system accepts as input a fuzzy vector all of whose components are fuzzy sets, and produces as output a tizzy set of conclusions. Non-fuzzy data are stored as fuzzy data with grade of membership one; internally, all data are considered fuz