English  |  正體中文  |  简体中文  |  Items with full text/Total items : 90069/105176 (86%)
Visitors : 6564292      Online Users : 171
RC Version 6.0 © Powered By DSPACE, MIT. Enhanced by NTU Library IR team.
Scope Tips:
  • please add "double quotation mark" for query phrases to get precise results
  • please goto advance search for comprehansive author search
  • Adv. Search
    HomeLoginUploadHelpAboutAdminister Goto mobile version


    Please use this identifier to cite or link to this item: http://asiair.asia.edu.tw/ir/handle/310904400/4717


    Title: Integrating membership functions and fuzzy rule sets from multiple knowledge sources
    Authors: C. H. Wang;T. P. Hong;S. S. Tseng
    Contributors: Department of Information Science and Applications
    Date: 2000-05
    Issue Date: 2009-11-30 16:03:15 (UTC+8)
    Publisher: Asia University
    Abstract: 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.
    Relation: Fuzzy Sets and System 112(1):141-154
    Appears in Collections:[行動商務與多媒體應用學系] 期刊論文

    Files in This Item:

    File Description SizeFormat
    0KbUnknown402View/Open
    310904400-4717.doc38KbMicrosoft Word313View/Open


    All items in ASIAIR are protected by copyright, with all rights reserved.


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