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Simple feedback logic, genetic algorithms and artificial neural networks for real-time control of a collection system
Hajda, P; Novotny, V; Feng, X; Yang, RL
1998
Source PublicationWATER SCIENCE AND TECHNOLOGY
ISSN0273-1223
Volume38Issue:3Pages:187-195
AbstractThis paper describes a pilot-scale implementation of a simple, real-time control (RTC) algorithm based on feedback and also outlines the development and simulation testing of a new RTC methodology that combines genetic algorithms (GAs) and artificial neural networks (ANNs). Computer simulations indicated that the simple feedback logic could reduce pumping by 50 to 80 percent if used to replace the existing RTC system in the test area. Experience with the algorithm after its implementation has confirmed the potential of the algorithm to reduce pumping. Additional simulations with an emerging approach to control (based on GAs) indicated possibilities of reducing pumping still further. Although relatively simple flow routing was used in the GAs, these algorithms do not restrict flow routing to any particular method. If highly accurate flow routing is incorporated, GAs are likely to be rendered too slow for on-line applications. Nevertheless, GAs can still be used, because they can be combined with fast executing on-line algorithms, such as ANNs. This possibility was demonstrated by training a multi-layer ANN to approximate one of the GAs developed. In verification runs the trained ANN provided virtually the same control decisions as did the GA used as the source of the training data. (C) 1998 Published by Elsevier Science Ltd. All rights reserved.
Keywordartificial neural networks combined sewer overflows genetic algorithms real-time control
Language英语
WOS Research AreaEngineering ; Environmental Sciences & Ecology ; Water Resources
WOS SubjectEngineering, Environmental ; Environmental Sciences ; Water Resources
WOS IDWOS:000077215400025
PublisherPERGAMON-ELSEVIER SCIENCE LTD
Citation statistics
Document Type期刊论文
Identifierhttp://ir.amss.ac.cn/handle/2S8OKBNM/13992
Collection中国科学院数学与系统科学研究院
Corresponding AuthorHajda, P
Affiliation1.Univ Wisconsin, Dept Civil & Environm Engn, Milwaukee, WI 53201 USA
2.Univ Wisconsin, Dept Elect & Comp Engn, Milwaukee, WI 53201 USA
3.Chinese Acad Sci, Inst Syst Sci, Beijing 100080, Peoples R China
Recommended Citation
GB/T 7714
Hajda, P,Novotny, V,Feng, X,et al. Simple feedback logic, genetic algorithms and artificial neural networks for real-time control of a collection system[J]. WATER SCIENCE AND TECHNOLOGY,1998,38(3):187-195.
APA Hajda, P,Novotny, V,Feng, X,&Yang, RL.(1998).Simple feedback logic, genetic algorithms and artificial neural networks for real-time control of a collection system.WATER SCIENCE AND TECHNOLOGY,38(3),187-195.
MLA Hajda, P,et al."Simple feedback logic, genetic algorithms and artificial neural networks for real-time control of a collection system".WATER SCIENCE AND TECHNOLOGY 38.3(1998):187-195.
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