基于LSTM深度学习的陕西泾河径流量及含沙量预测方法研究

Cite this article:	同套文.基于LSTM深度学习的陕西泾河径流量及含沙量预测方法研究[J].灌溉排水学报,,():-.
	tongtaowen.基于LSTM深度学习的陕西泾河径流量及含沙量预测方法研究[J].灌溉排水学报,,():-.

This article has been：Browse 1948Times Download 0Times
Font:+\|=\|-
DOI：

study on the prediction method of run off and sediment concentration of Jinghe River in Shanxi Province Based on LSTM deep learning
tongtaowen
jiaokou pumping irrigation Adninistration Bureau of Shanxi Province
Abstract:
A time series prediction method based on long-term memory neural network is proposed,It provides a reliable theoretical basis for flood control and water resources utilization.
Key words: LSTM deep learning correlation analysis forecast verification