Please use this identifier to cite or link to this item:
https://scholarbank.nus.edu.sg/handle/10635/111247
DC Field | Value | |
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dc.title | Emulating human decision making process using hybrid system | |
dc.contributor.author | Quah, T.S. | |
dc.contributor.author | Teh, H.H. | |
dc.contributor.author | Tan, C.L. | |
dc.date.accessioned | 2014-11-27T09:46:11Z | |
dc.date.available | 2014-11-27T09:46:11Z | |
dc.date.issued | 1995 | |
dc.identifier.citation | Quah, T.S.,Teh, H.H.,Tan, C.L. (1995). Emulating human decision making process using hybrid system. IEEE International Conference on Neural Networks - Conference Proceedings 4 : 1823-1827. ScholarBank@NUS Repository. | |
dc.identifier.uri | http://scholarbank.nus.edu.sg/handle/10635/111247 | |
dc.description.abstract | This paper presents the prototype implementation of a hybrid neural network expert system shell. The shell, 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. Furthermore, the firing of netels emulate opportunistic decision making process, which is typical of human decision makers. Finally, the system is also able to adjust its inference strategy according to different users and situations. | |
dc.source | Scopus | |
dc.type | Conference Paper | |
dc.contributor.department | INFORMATION SYSTEMS & COMPUTER SCIENCE | |
dc.contributor.department | INSTITUTE OF SYSTEMS SCIENCE | |
dc.description.sourcetitle | IEEE International Conference on Neural Networks - Conference Proceedings | |
dc.description.volume | 4 | |
dc.description.page | 1823-1827 | |
dc.description.coden | ICNNF | |
dc.identifier.isiut | NOT_IN_WOS | |
Appears in Collections: | Staff Publications |
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