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作者:

Yang, Zhuang (Yang, Zhuang.) | Yang, Cuili (Yang, Cuili.) | Qiao, Junfei (Qiao, Junfei.) (学者:乔俊飞)

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EI Scopus

摘要:

In the sewage treatment process, the dissolved oxygen concentration is a very important control target, but it is difficult to be controlled. To solve this problem, a self-organizing fuzzy neural network controller based on genetic ideas (G-SOFNN) is proposed. In the controller structure reduction process, the deleted neuron information is merged with the remaining neurons to reduce the interference set. During the controller structure increasing phase, the information of new neurons is initialized to avoid overlapping of information. Then, the controller parameters are trained by the projection algorithm to improve the control precision. Experiments illustrate that the proposed method can accurately control the concentration of dissolved oxygen in the sewage treatment process. © 2019, ICST Institute for Computer Sciences, Social Informatics and Telecommunications Engineering.

关键词:

Controllers Dissolved oxygen Fuzzy inference Fuzzy logic Fuzzy neural networks Machine learning Neurons Process control Sewage treatment

作者机构:

  • [ 1 ] [Yang, Zhuang]Faculty of Information Technology, Beijing Key Laboratory of Computational Intelligence and Intelligent System, Beijing University of Technology, Beijing; 100124, China
  • [ 2 ] [Yang, Cuili]Faculty of Information Technology, Beijing Key Laboratory of Computational Intelligence and Intelligent System, Beijing University of Technology, Beijing; 100124, China
  • [ 3 ] [Qiao, Junfei]Faculty of Information Technology, Beijing Key Laboratory of Computational Intelligence and Intelligent System, Beijing University of Technology, Beijing; 100124, China

通讯作者信息:

  • [yang, zhuang]faculty of information technology, beijing key laboratory of computational intelligence and intelligent system, beijing university of technology, beijing; 100124, china

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来源 :

ISSN: 1867-8211

年份: 2019

卷: 294 LNCIST

页码: 636-644

语种: 英文

被引次数:

WoS核心集被引频次: 0

SCOPUS被引频次: 1

ESI高被引论文在榜: 0 展开所有

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