Hybrid Neural Network and Expert Systems by Larry R. Medsker.

Hybrid Neural Network and Expert Systems presents the basics of expert systems and neural networks, and the important characteristics relevant to the integration of these two technologies. Through case studies of actual working systems, the author demonstrates the use of these hybrid systems in prac...

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Bibliographic Details
Main Author: Medsker, Larry R. (Author)
Corporate Author: SpringerLink (Online service)
Format: eBook
Language:English
Published: New York, NY : Springer US : Imprint: Springer, 1994.
Edition:1st ed. 1994.
Series:Springer eBook Collection.
Subjects:
Online Access:Click to view e-book
Holy Cross Note:Loaded electronically.
Electronic access restricted to members of the Holy Cross Community.
Description
Summary:Hybrid Neural Network and Expert Systems presents the basics of expert systems and neural networks, and the important characteristics relevant to the integration of these two technologies. Through case studies of actual working systems, the author demonstrates the use of these hybrid systems in practical situations. Guidelines and models are described to help those who want to develop their own hybrid systems. 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.
Physical Description:XII, 240 p. online resource.
ISBN:9781461527268
DOI:10.1007/978-1-4615-2726-8