Short-term power load forecasting based on EEMD-SE and RBF optimized by genetic algorithm

Short-term power load forecasting based on EEMD-SE and RBF optimized by genetic algorithm

In order to improve the forecasting accuracy of short-term power load，a power load forecasting approach based on ensemble empirical mode decomposition(EEMD)-sample entropy(SE) and genetic algorithm(GA) for RBF neural network optimization is proposed in the paper. The EEMD decomposition method is use...

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Bibliographic Details
Main Authors: Gao Qiang, Li Yilong, Li Dahua, Bai Zixuan
Format: Article
Language:zho
Published: National Computer System Engineering Research Institute of China 2019-01-01
Series:Dianzi Jishu Yingyong
Subjects:
load forecasting
ensemble empirical mode decomposition
genetic algorithm
neural network
sample entropy
Online Access:http://www.chinaaet.com/article/3000096409

Internet

http://www.chinaaet.com/article/3000096409

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