| Summary: | 碩士 === 國立暨南國際大學 === 資訊管理學系 === 92 === As domain knowledge has played an important role for various applications, such as the development of intelligent systems and decision-support systems, the issues concerning knowledge acquisition and knowledge management have attracted researchers from many fields. Furthermore, the lead-in of fuzzy theory has strengthened the power of knowledge representation and reasoning in expert systems. While collecting knowledge from multiple knowledge sources, a variety of logical problems might occur, e.g., redundancy, conflict, circularity and incompleteness, which will lead to incorrect decisions and affect the efficiency of the expert systems. In this thesis, we attempt to detect potential anomalies among fuzzy rules by proposing a fuzzy rule verification algorithm. Moreover, a fuzzy knowledge base verification system has been developed based on the novel approach.
Keyword: artificial intelligence, expert systems, knowledge verification, fuzzy logic, knowledge base
|
|---|
