ASIA unversity:Item 310904400/4717
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    题名: Integrating membership functions and fuzzy rule sets from multiple knowledge sources
    作者: C. H. Wang;T. P. Hong;S. S. Tseng
    贡献者: Department of Information Science and Applications
    日期: 2000-05
    上传时间: 2009-11-30 16:03:15 (UTC+8)
    出版者: Asia University
    摘要: In this paper, we propose a GA-based fuzzy knowledge-integration framework that can simultaneously integrate multiple fuzzy rule sets and their membership function sets. The proposed two-phase approach includes fuzzy knowledge encoding and fuzzy knowledge integration. In the encoding phase, each fuzzy rule set with its associated membership functions is first transformed into an intermediary representation, and further encoded as a string. The combined strings form an initial knowledge population, which is then ready for integration. In the knowledge-integration phase, a genetic algorithm is used to generate an optimal or nearly optimal set of fuzzy rules and membership functions from the initial knowledge population. The hepatitis diagnostic problem was used to show the performance of the proposed knowledge-integration approach. Results show that the fuzzy knowledge-base resulting from using our approach performs better than every individual knowledge base.
    關聯: Fuzzy Sets and System 112(1):141-154
    显示于类别:[行動商務與多媒體應用學系] 期刊論文

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