Enhanced LSTM Model for Daily Runoff Prediction in the Upper Huai River Basin, China-Reference-Cited by-同舟云学术

Enhanced LSTM Model for Daily Runoff Prediction in the Upper Huai River Basin, China

Published:2022-04 Issue: Volume: Page:
ISSN:2095-8099
Container-title:Engineering
language:en
Short-container-title:Engineering

Author:

Man Yuanyuan,Yang Qinli,Shao Junming,Wang Guoqing,Bai Linlong,Xue Yunhong

Publisher

Elsevier BV

Subject

General Engineering,Energy Engineering and Power Technology,Materials Science (miscellaneous),General Chemical Engineering,Environmental Engineering,General Computer Science

Reference57 articles.

1. Needed: a systems approach to improve flood risk mitigation through private precautionary measures;Barendrecht;Water Secur,2020

2. Forecasting for flood warning;Moore;C R Geosci,2005

3. Measuring the skill of an operational ice jam flood forecasting system;Williams;Int J Disast Risk Re,2021

4. Economic losses, poverty and disasters 1998–2017;Mizutori,2018

5. Flood protection and management: quo vadimus?;Kundzewicz;Hydrol Sci J,1999

Cited by 21 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Runoff prediction based on the IGWOLSTM model: Achieving accurate flood forecasting and emergency management;Journal of Hydro-environment Research;2024-09

2. Incorporating hydrological constraints with deep learning for streamflow prediction;Expert Systems with Applications;2024-09

3. Application of a Multi-Model Fusion Forecasting Approach in Runoff Prediction: A Case Study of the Yangtze River Source Region;Sustainability;2024-07-12

4. Spatio-temporal deep learning model for accurate streamflow prediction with multi-source data fusion;Environmental Modelling & Software;2024-07

5. The role of matching pursuit algorithm and multi-scale daily rainfall data obtained from decomposition in runoff prediction;Journal of Hydrology: Regional Studies;2024-06