Please use this identifier to cite or link to this item: http://hdl.handle.net/20.500.11861/7722
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dc.contributor.authorProf. LEUNG Kwong Saken_US
dc.contributor.authorWong, W.S. Felixen_US
dc.contributor.authorLam W.en_US
dc.date.accessioned2023-03-31T04:41:55Z-
dc.date.available2023-03-31T04:41:55Z-
dc.date.issued1989-
dc.identifier.citationExpert Systems, 1989, vol. 6 (1), pp. 2 - 10en_US
dc.identifier.issn02664720-
dc.identifier.urihttp://hdl.handle.net/20.500.11861/7722-
dc.description.abstractAbstract: Much of the information resident in the knowledge base of a typical expert system is imprecise, incomplete or not totally reliable. The special features of a novel expert system shell based on fuzzy logic and numbers are presented. This rule‐based system can deal with exact, inexact (fuzzy) and combined reasoning as well as uncertainty represented by fuzzy numbers. Natural language interface is built in naturally using fuzzy logic representation. Several application areas, namely, classification, risk analysis and information retrieval, are discussed with four appropriate sample expert systems actually built using this shell. Through these expert systems, the additional power and advantages over traditional expert systems are illustrated. It has been demonstrated that the introduction of fuzzy concepts into expert systesms is not feasible but highly desirable. Copyright © 1989, Wiley Blackwell. All rights reserveden_US
dc.language.isoenen_US
dc.relation.ispartofExpert Systemsen_US
dc.titleApplications of a novel fuzzy expert system shellen_US
dc.typePeer Reviewed Journal Articleen_US
dc.identifier.doi10.1111/j.1468-0394.1989.tb00070.x-
item.fulltextNo Fulltext-
crisitem.author.deptDepartment of Applied Data Science-
Appears in Collections:Applied Data Science - Publication
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