Study on the Improvement of the Application of Complete Ensemble Empirical Mode Decomposition with Adaptive Noise in Hydrology Based on RBFNN Data Extension Technology-Reference-Cited by-同舟云学术

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Study on the Improvement of the Application of Complete Ensemble Empirical Mode Decomposition with Adaptive Noise in Hydrology Based on RBFNN Data Extension Technology

Published:2021 Issue:2 Volume:126 Page:755-770
ISSN:1526-1506
Container-title:Computer Modeling in Engineering & Sciences
language:en
Short-container-title:

Author:

Zhang Jinping,Jin Youlai,Sun Bin,Han Yuping,Hong Yang

Publisher

Computers, Materials and Continua (Tech Science Press)

Subject

Computer Science Applications,Modelling and Simulation,Software

Link

https://www.techscience.com/CMES/v126n2/41284/pdf

Cited by 4 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. A Combination Prediction Model for Short Term Travel Demand of Urban Taxi;Computers, Materials & Continua;2024

2. Study on Temporal Variability of Hydrological Elements in the Daqing River Basin, China;Journal of Hydrologic Engineering;2023-11

3. Structural Damage Identification Using Ensemble Deep Convolutional Neural Network Models;Computer Modeling in Engineering & Sciences;2023

4. Stepwise decomposition-integration-prediction framework for runoff forecasting considering boundary correction;Science of The Total Environment;2022-12

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