Research and Application of a Hybrid Forecasting Model Based on Data Decomposition for Electrical Load Forecasting-Reference-Cited by-同舟云学术

Research and Application of a Hybrid Forecasting Model Based on Data Decomposition for Electrical Load Forecasting

Published:2016-12-14 Issue:12 Volume:9 Page:1050
ISSN:1996-1073
Container-title:Energies
language:en
Short-container-title:Energies

Author:

Dong Yuqi,Ma Xuejiao^ORCID,Ma Chenchen,Wang Jianzhou

Funder

National Natural Science Foundation of China

Publisher

MDPI AG

Subject

Energy (miscellaneous),Energy Engineering and Power Technology,Renewable Energy, Sustainability and the Environment,Electrical and Electronic Engineering,Control and Optimization,Engineering (miscellaneous)

Link

http://www.mdpi.com/1996-1073/9/12/1050/pdf

Reference45 articles.

1. Modelling a combined method based on ANFIS and neural network improved by DE algorithm: A case study for short-term electricity demand forecasting

2. An ensemble approach for short-term load forecasting by extreme learning machine

3. Using the ensemble Kalman filter for electricity load forecasting and analysis

4. A combined model based on data pre-analysis and weight coefficients optimization for electrical load forecasting

5. Random vector functional link network for short-term electricity load demand forecasting

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