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This book tackles two concerns of knowledge engineers in designing and developing a fuzzy rulebased expert system (FES). First is to acquire a knowledgebase that emulates human perception of application domain concept in order to avoid sharp boundary problems. Second is the need for modelling a comprehensive fuzzy rulebased expert system which eliminates redundant rules in order to solve the problem of rulebase unwieldiness and provide for knowledgebase instant updates. This book introduces Fuzzy Association Rule Mining ExpertDriven (FARMED) approach to knowledge acquisition. In doing this, the Apriorilike Fuzzy Association Rule Mining algorithm was adopted. Adopting FARMED automated knowledge acquisition in modelling fuzzy expert system eliminates redundant rules and save memory usage. The rules generated based on expertdriven approach correspond to human perception of the application domain as compared to datadriven approach. Also, the integration of FARMED approach to standard fuzzy expert system architecture provides for knowledgebase instant updates and resulted in a novel architecture called Fuzzy Association Rule Mining Expert System (FARMES).
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