Research on Runoff Flow Prediction Based on Variational Mode Decomposition and PSO-SVM Model-Reference-Cited by-同舟云学术

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Research on Runoff Flow Prediction Based on Variational Mode Decomposition and PSO-SVM Model

Published:2023-12-15 Issue: Volume: Page:3770-3775
ISSN:
Container-title:2023 IEEE 7th Conference on Energy Internet and Energy System Integration (EI2)
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Author:

Zhou Ping¹,Yang Dongwei¹,Wang Rongxin²,Yang Sihao³,Guo Song⁴

Affiliation:

1. School of hydraulic & Ecological Engineering, Nanchang Institute of Technology,Nanchang,China

2. Qilian Water Resource Conservation Forests Research Institute,Forestry and Grassland Bureau of Zhangye City,Zhangye,China

3. Jiangxi Provincial Natural Resources Policy Survey and Evaluation Center,Department of Natural Resources of Jiangxi Province,Nanchang,China

4. Jiangxi Province Institute of Water Sciences,Jiangxi Provincial Technology Innovation Center for Ecological Water Engineering in Poyang Lake Basin,Nanchang,China

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/10511272/10512350/10512438.pdf?arnumber=10512438

Reference11 articles.

1. An Integrated Statistical-Machine Learning Approach for Runoff Prediction

2. Runoff Prediction under Different Precipitation Scenarios Based on SWAT Model and Stochastic Simulation of Precipitation

3. Process-based hydrological modelling: The potential of a bottom-up approach for runoff predictions in ungauged catchments

4. Monthly Streamflow Forecasting Using Decomposition-Based Hybridization with Two-step Verification Method Over the Mangla Watershed, Pakistan

5. A Hybrid Model for Runoff Prediction Using Variational Mode Decomposition and Artificial Neural Network

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