Please use this identifier to cite or link to this item:
Title: Neural network expert system shell
Authors: Quah, Tong-Seng 
Tan, Chew-Lim 
Teh, Hoon-Heng 
Issue Date: 1994
Citation: Quah, Tong-Seng,Tan, Chew-Lim,Teh, Hoon-Heng (1994). Neural network expert system shell. Proceedings of the Conference on Artificial Intelligence Applications : 502-508. ScholarBank@NUS Repository.
Abstract: This paper presents the architecture of a hybrid neural network expert system shell. The system, structured around the concept of 'network element', is aimed at preserving semantic structure of the expert system rules whilst incorporating learning capability of neural networks into the inferencing mechanism. Using this architecture, every rule of the knowledge base is represented by a one or two-layer neural network element. These network elements are dynamically linked up to form the rule-tree during inferencing process. The system is also able to adjust its inference strategy according to different users and situations. A rule editor is also provided to enable easy maintenance of the neural network rule elements.
Source Title: Proceedings of the Conference on Artificial Intelligence Applications
ISBN: 081865550X
Appears in Collections:Staff Publications

Show full item record
Files in This Item:
There are no files associated with this item.

Google ScholarTM



Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.