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Table of contents (11 chapters)
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Front Matter
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Fundamentals of Hybrid Systems
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Front Matter
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Case Studies of Hybrid Neural Network and Expert Systems
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Front Matter
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Analysis and Guidelines
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Front Matter
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Back Matter
About this book
Neural networks and expert systems together represent two major aspects of human intelligence and therefore are appropriate for integration. Neural networks represent the visual, pattern-recognition types of intelligence, while expert systems represent the logical, reasoning processes. Together, these technologies allow applications to be developed that are more powerful than when each technique is used individually.
Hybrid Neural Network and Expert Systems provides frameworks for understanding how the combination of neural networks and expert systems can produce useful hybrid systems, and illustrates the issues and opportunities in this dynamic field.
Authors and Affiliations
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Department of Computer Science and Information Systems, The American University, USA
Larry R. Medsker
Bibliographic Information
Book Title: Hybrid Neural Network and Expert Systems
Authors: Larry R. Medsker
DOI: https://doi.org/10.1007/978-1-4615-2726-8
Publisher: Springer New York, NY
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eBook Packages: Springer Book Archive
Copyright Information: Springer Science+Business Media New York 1994
Hardcover ISBN: 978-0-7923-9423-5Published: 31 December 1993
Softcover ISBN: 978-1-4613-6175-6Published: 08 October 2012
eBook ISBN: 978-1-4615-2726-8Published: 06 December 2012
Edition Number: 1
Number of Pages: XII, 240
Topics: Artificial Intelligence, Complex Systems, Systems Theory, Control, Statistical Physics and Dynamical Systems