A CNN-BILSTM monthly rainfall prediction model based on SCSSA optimization

Meteorological conditions play an important role in China's national production, and the accurate prediction of precipitation is of great significance for social production, flood prevention, and the protection of people's lives and property. A coupled model for monthly rainfall prediction...

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Veröffentlicht in:	Journal of water and climate change Jg. 15; H. 9; S. 4862 - 4876
Hauptverfasser:	Zhang, Xianqi, Yang, Yang, Liu, Jiawen, Zhang, Yuehan, Zheng, Yupeng
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	London IWA Publishing 01.09.2024
Schlagworte:	Accuracy Agricultural production Algorithms Artificial neural networks Flood control Flood management Flood predictions Flood prevention Hydrologic data Hydrologic models Hydrology Meteorological conditions Monthly rainfall Monthly rainfall data Neural networks Optimization Optimization algorithms Precipitation Prediction models Rainfall Rainfall forecasting Runoff Simulation Wavelet transforms
ISSN:	2040-2244, 2408-9354
Online-Zugang:	Volltext
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