A Novel mRMR-RFE-RF Method for Enhancing Medium- and Long-Term Hydrological Forecasting: A Case Study of the Danjiangkou Basin
Author:
Affiliation:
1. College of Telecommunications and Information Engineering, Nanjing University of Posts and Telecommunications, Nanjing, China
2. Nanjing Hydraulic Research Institute, Hydrology and Water Resources Department, Nanjing, China
Funder
Natural Science Research Start-up Foundation of Recruiting Talents of Nanjing University of Posts and Telecommunications
Belt and Road Special Foundation of The National Key Laboratory of Water Disaster Prevention
Natural Science Foundation of Jiangsu Province, China
Publisher
Institute of Electrical and Electronics Engineers (IEEE)
Link
http://xplorestaging.ieee.org/ielx8/4609443/10330207/10646493.pdf?arnumber=10646493
Reference55 articles.
1. Hydrologically Informed Machine Learning for Rainfall‐Runoff Modeling: A Genetic Programming‐Based Toolkit for Automatic Model Induction
2. Research on flood forecasting based on flood hydrograph generalization and random forest in Qiushui River basin, China
3. A Transdisciplinary Review of Deep Learning Research and Its Relevance for Water Resources Scientists
4. Nationwide Radar-Based Precipitation Nowcasting—A Localization Filtering Approach and its Application for Germany
5. Soil Moisture Retrieval From Multipolarization SAR Data and Potential Hydrological Application
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