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    Please use this identifier to cite or link to this item: https://ir.fy.edu.tw:8080/ir/handle/987654321/10062


    Title: Rough Set-Based Hybrid Fuzzy-Neural Controller Design for Industrial Wastewater Treatment
    Authors: Chen,W. C.;Chang,Ni-Bin;Chen, Jeng-Chung
    Contributors: 輔英科技大學 環境工程與科學系
    Keywords: Optimal control;Rough set;Genetic algorithm;Neural network;Fuzzy logic control;Wastewater treatment;Artificial intelligence;Soft computing;Knowledge discovery;Machine learning
    Date: 2003-01
    Issue Date: 2010-11-17 16:27:10 (UTC+8)
    Abstract: Recent advances in control engineering suggest that hybrid control strategies, integrating some ideas and paradigms existing in different soft computing techniques, such as fuzzy logic, genetic algorithms, rough set theory, and neural networks, may provide improved control performance in wastewater treatment processes. This paper presents an innovative hybrid control algorithm leading to integrate the distinct aspects of indiscernibility capability of rough set theory and search capability of genetic algorithms with conventional neural-fuzzy controller design. The methodology proposed in this study employs a three-stage analysis that is designed in series for generating a representative state function, searching for a set of multi-objective control strategies, and performing a rough set-based autotuning for the neural-fuzzy logic controller to make it applicable for controlling an industrial wastewater treatment process. Research findings in the case study clearly indicate that the use of rough set theory to aid in the neural-fuzzy logic controller design can produce relatively better plant performance in terms of operating cost, control stability, and response time simultaneously, which is effective at least in the selected industrial wastewater treatment plant. Such a methodology is anticipated to be capable of dealing with many other types of process control problems in waste treatment processes by making only minor modifications.
    Relation: Water Research,Volume 37, Issue 1, Pages 95-107
    Appears in Collections:[環境工程與科學系] 期刊論文

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