| Issue |
E3S Web Conf.
Volume 360, 2022
2022 8th International Symposium on Vehicle Emission Supervision and Environment Protection (VESEP2022)
|
|
|---|---|---|
| Article Number | 01093 | |
| Number of page(s) | 6 | |
| DOI | https://doi.org/10.1051/e3sconf/202236001093 | |
| Published online | 23 November 2022 | |
Research on drought prediction model of LSTM with elevation of water
Wuhan Britain-China School, No.10 Gutian Ce Rd., Qiaokou District, Wuhan, Hubei, P.R. China
* Corresponding author: 2962860955@qq.com
The Drought is one of the most widespread and damaging natural phenomena in the world and have been increasing around the world in recent years. A drought is a persistent shortage of water caused by an imbalance in water supply and demand. The water shortage can be manifested as insufficient precipitation, lack of soil moisture or low elevation of water of rivers and lakes. So, in this paper, according to the recent drought period and the elevation of water data of Lake Mead, the drought prediction model of the elevation of water used long short-term memory (LSTM) neural network was established to predict the elevation of water of Lake Mead in 2025, 2030, and 2050 and drought prediction respectively. The results show that the drought prediction model of the elevation of water used LSTM has the high accuracy in the data set.
Key words: Elevation of water / Lake Mead / LSTM / Drought prediction
© The Authors, published by EDP Sciences, 2022
This is an Open Access article distributed under the terms of the Creative Commons Attribution License 4.0 (http://creativecommons.org/licenses/by/4.0/).
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