Integration of deep learning and improved multi-objective algorithm to optimize reservoir operation for balancing human and downstream ecological needs

•A multi-objective simulation-optimization (MOSO) framework optimizes reservoir operation.•Trade-offs among hydropower generation, ecological flow and ecological water temperature demands are achieved.•LSTM_1DCNN outperforms conventional LSTM in predicting dam discharge temperature.•ε-MOACOR provide...

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Vydané v:	Water research (Oxford) Ročník 253; s. 121314
Hlavní autori:	Qiu, Rujian, Wang, Dong, Singh, Vijay P., Wang, Yuankun, Wu, Jichun
Médium:	Journal Article
Jazyk:	English
Vydavateľské údaje:	England Elsevier Ltd 01.04.2024
Predmet:	Algorithms Animals Deep Learning domain Ecological flow Ecosystem fish Humans Models, Theoretical Multi-objective trade-offs neural networks power generation Reservoir optimization operation system optimization Water water power Water temperature Multi-objective trade-offs Deep learning Reservoir optimization operation Water temperature Ecological flow
ISSN:	0043-1354, 1879-2448, 1879-2448
On-line prístup:	Získať plný text
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