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231224s2013 xx |||||o 00| ||eng c |
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|a 10.2166/wst.2012.563
|2 doi
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|a pubmed25n0743.xml
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|a eng
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|a Huang, Xiaoqi
|e verfasserin
|4 aut
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|a Energy consumption model for wastewater treatment process control
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|c 2013
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|a Text
|b txt
|2 rdacontent
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|a ƒaComputermedien
|b c
|2 rdamedia
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|a ƒa Online-Ressource
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|2 rdacarrier
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|a Date Completed 18.03.2013
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|a Date Revised 07.12.2022
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|a published: Print
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|a Citation Status MEDLINE
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|a Wastewater treatment must satisfy discharge requirements under specified constraints and have minimal operating costs (OC). The operating results of wastewater treatment processes (WWTPs) have significantly focused on both the energy consumption (EC) and effluent quality (EQ). To reflect the relationship between the EC and EQ of WWTPs directly, an extended Elman neural network-based energy consumption model (EENN-ECM) was studied for WWTP control in this paper. The proposed EENN-ECM was capable of predicting EC values in the treatment process. Moreover, the self-adaptive characteristic of the EENN ensured the modeling accuracy. A performance demonstration was carried out through a comparison of the EC between the benchmark simulation model No.1 (BSM1) and the EENN-ECM. The experimental results demonstrate that this EENN-ECM is more effective to model the EC of WWTPs
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|a Journal Article
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|a Research Support, Non-U.S. Gov't
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|a Waste Water
|2 NLM
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| 700 |
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|a Han, Honggui
|e verfasserin
|4 aut
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|a Qiao, Junfei
|e verfasserin
|4 aut
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| 773 |
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|i Enthalten in
|t Water science and technology : a journal of the International Association on Water Pollution Research
|d 1986
|g 67(2013), 3 vom: 30., Seite 667-74
|w (DE-627)NLM098149431
|x 0273-1223
|7 nnns
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| 773 |
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|g volume:67
|g year:2013
|g number:3
|g day:30
|g pages:667-74
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|u http://dx.doi.org/10.2166/wst.2012.563
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|d 67
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|h 667-74
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