"Covering the latest issues and achievements, this well documented, precisely presented text is timely and suitable for graduate and upper undergraduate students in knowledge engineering, intelligent systems, AI, neural networks, fuzzy systems, and related areas. The author's goal is to explain
Foundations of neural networks, fuzzy systems, and knowledge engineering
โ Scribed by Nikola K. Kasabov
- Publisher
- The MIT Press
- Year
- 1996
- Tongue
- English
- Leaves
- 581
- Series
- American Men and Women of Science
- Edition
- 22
- Category
- Library
No coin nor oath required. For personal study only.
โฆ Synopsis
Neural networks and fuzzy systems are different approaches to introducing human-like reasoning into expert systems. This text is the first to combine the study of these two subjects, their basics and their use, along with symbolic AI methods to build comprehensive artificial intelligence systems.In a clear and accessible style, Kasabov describes rule- based and connectionist techniques and then their combinations, with fuzzy logic included, showing the application of the different techniques to a set of simple prototype problems, which makes comparisons possible. A particularly strong feature of the text is that it is filled with applications in engineering, business, and finance. AI problems that cover most of the application-oriented research in the field (pattern recognition, speech and image processing, classification, planning, optimization, prediction, control, decision making, and game simulations) are discussed and illustrated with concrete examples.
โฆ Subjects
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๐ SIMILAR VOLUMES
Neural networks and fuzzy systems are different approaches to introducing human-like reasoning into expert systems. This text is the first to combine the study of these two subjects, their basics and their use, along with symbolic AI methods to build comprehensive artificial intelligence systems.
Provides an up-to-date integration of expert systems with fuzzy logic and neural networks. * Includes coverage of simulation models not present in other books. * Presents cases and examples taken from the authors' experience in research and applying the technology to real-world situations.
Provides an up-to-date integration of expert systems with fuzzy logic and neural networks.Includes coverage of simulation models not present in other books.Presents cases and examples taken from the authors' experience in research and applying the technology to real-world situations.
Although fuzzy systems and neural networks stand central to the field of soft computing, most research work has focused on the development of the theories, algorithms, and designs of systems for specific applications. There has been little theoretical support for fuzzy neural systems, especially the