Dynamic optimization of wastewater treatment process based on novel multi-objective ant lion optimization and deep learning algorithm

In this paper, a novel dynamic optimization control based on multi-objective ant lion optimization (DMOALO) and deep learning algorithm is proposed, which could optimize energy consumption (EC) and effluent quality (EQ) simultaneously in the wastewater treatment processes. In order to overcome the d...

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Vydáno v:	Journal of cleaner production Ročník 345; s. 131140
Hlavní autoři:	Niu, Guoqiang, Li, Xiaoyong, Wan, Xin, He, Xinzhong, Zhao, Yinzhong, Yi, Xiaohui, Chen, Chen, Xujun, Liang, Ying, Guangguo, Huang, Mingzhi
Médium:	Journal Article
Jazyk:	angličtina
Vydáno:	Elsevier Ltd 15.04.2022
Témata:	algorithms carbon Carbon neutrality Deep belief network Dynamic multi-objective ant lion optimization energy Myrmeleontidae simulation models Wastewater activated sludge treatment processes wastewater treatment Wastewater activated sludge treatment processes Carbon neutrality Deep belief network Dynamic multi-objective ant lion optimization
ISSN:	0959-6526, 1879-1786
On-line přístup:	Získat plný text
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