English  |  正體中文  |  简体中文  |  Items with full text/Total items : 6047/14565 (42%)
Visitors : 13677573      Online Users : 355
RC Version 7.0 © 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: https://ir.fy.edu.tw:8080/ir/handle/987654321/10045


    Title: Mining the fuzzy control rules of aeration in a Submerged Biofilm Wastewater Treatment Process
    Authors: Chen, Jeng-Chung;Chang, Ni-Bin
    Contributors: 輔英科技大學 環境工程與科學系
    Keywords: Neural networks;Fuzzy logic control;Hybrid approach;Process control;Wastewater treatment
    Date: 2007-10
    Issue Date: 2010-11-16 17:38:12 (UTC+8)
    Abstract: This paper presents a special rule base extraction analysis for optimal design of an integrated neural-fuzzy process controller using an “impact assessment approach.” It sheds light on how to avoid some unreasonable fuzzy control rules by screening inappropriate fuzzy operators and reducing over fitting issues simultaneously when tuning parameter values for these prescribed fuzzy control rules. To mitigate the design efforts, the self-learning ability embedded in the neural networks model was emphasized for improving the rule extraction performance. An aeration unit in an Aerated Submerged Biofilm Wastewater Treatment Process (ASBWTP) was picked up to support the derivation of a solid fuzzy control rule base. Four different fuzzy operators were compared against one other in terms of their actual performance of automated knowledge acquisition in the system based on a partial or full rule base prescribed. Research findings suggest that using bounded difference fuzzy operator (Ob) in connection with back propagation neural networks (BPN) algorithm would be the best choice to build up this feedforward fuzzy controller design.
    Relation: Engineering Applications of Artificial Intelligence,Volume 20, Issue 7, Pages 959-969
    Appears in Collections:[環境工程與科學系] 期刊論文

    Files in This Item:

    File Description SizeFormat
    index.html0KbHTML457View/Open


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


    本網站典藏內容為學術研究目的之提供,請尊重著作權人之權益合理使用,請勿任意重製、轉貼、改作及散佈。

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