Water resource forecasting with machine learning and deep learning: A scientometric analysis-Reference-Cited by-同舟云学术

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Water resource forecasting with machine learning and deep learning: A scientometric analysis

Published:2024-12 Issue: Volume:5 Page:100084
ISSN:2666-5441
Container-title:Artificial Intelligence in Geosciences
language:en
Short-container-title:Artificial Intelligence in Geosciences

Author:

Liu Chanjuan^ORCID,Xu Jing,Li Xi’an^ORCID,Yu Zhongyao,Wu Jinran^ORCID

Funder

Hubei Key Laboratory of Disaster Prevention and Mitigation

National Natural Science Foundation of China-Nuclear Technology Innovation Joint Fund

Ministry of Education Science and Technology Industry-University Cooperation and Education Project

Shanghai Lingjun Program

Publisher

Elsevier BV

Reference23 articles.

1. Evolution and hotspots of peer instruction: A visualized analysis using citespace;Bicheng;Educ. Inf. Technol.,2023

2. Water table depth forecasting in cranberry fields using two decision-tree-modeling approaches;Brédy;Agricult. Water. Manag.,2020

3. Real-time multi-step-ahead water level forecasting by recurrent neural networks for urban flood control;Chang;J. Hydrol.,2014

4. Advances in hydrologic forecasts and water resources management;Chang;Water,2020

5. Citespace II: Detecting and visualizing emerging trends and transient patterns in scientific literature;Chen;J. Am. Soc. Inf. Sci. Technol.,2006

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