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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Veröffentlicht in:	Water research (Oxford) Jg. 253; S. 121314
Hauptverfasser:	Qiu, Rujian, Wang, Dong, Singh, Vijay P., Wang, Yuankun, Wu, Jichun
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	England Elsevier Ltd 01.04.2024
Schlagworte:	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
Online-Zugang:	Volltext
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