ASIA unversity:Item 310904400/4717
English  |  正體中文  |  简体中文  |  全文笔数/总笔数 : 90570/105786 (86%)
造访人次 : 16362776      在线人数 : 346
RC Version 6.0 © Powered By DSPACE, MIT. Enhanced by NTU Library IR team.
搜寻范围 查询小技巧:
  • 您可在西文检索词汇前后加上"双引号",以获取较精准的检索结果
  • 若欲以作者姓名搜寻,建议至进阶搜寻限定作者字段,可获得较完整数据
  • 进阶搜寻


    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


    档案 描述 大小格式浏览次数
    310904400-4717.doc38KbMicrosoft Word333检视/开启


    DSpace Software Copyright © 2002-2004  MIT &  Hewlett-Packard  /   Enhanced by   NTU Library IR team Copyright ©   - 回馈