Runoff Prediction and Analysis Based on Improved CEEMDAN-OS-QR-ELM

Runoff Prediction and Analysis Based on Improved CEEMDAN-OS-QR-ELM

To solve the problems of low prediction accuracy, poor stability, and low calculation efficiency in runoff forecasting, this study develops an extreme learning machine (ELM) model based on improved complete ensemble empirical mode decomposition adaptive noise (CEEMDAN). The model first uses orthogon...

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Bibliographic Details
Main Authors: Yang Liu, Lihu Wang, Libo Yang, Xuemei Liu, Lingchen Wang
Format: Article
Language:English
Published: IEEE 2021-01-01
Series:IEEE Access
Subjects:
Runoff prediction
extreme learning machine
CEEMDAN
parallel calculation
Online Access:https://ieeexplore.ieee.org/document/9400823/

Internet

https://ieeexplore.ieee.org/document/9400823/

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