Forecasting China’s Renewable Energy Terminal Power Consumption Based on Empirical Mode Decomposition and an Improved Extreme Learning Machine Optimized by a Bacterial Foraging Algorithm

Forecasting China’s Renewable Energy Terminal Power Consumption Based on Empirical Mode Decomposition and an Improved Extreme Learning Machine Optimized by a Bacterial Foraging Algorithm

The energy consumption pattern dominated by traditional fossil energy has led to global energy resource constraints and the deterioration of the ecological environment. These challenges have become a major issue all over the world. At present, the Chinese government aims to significantly reduce the...

書誌詳細
主要な著者:	Peng Jiang, Jun Dong, Hui Huang
フォーマット:	論文
言語:	English
出版事項:	MDPI AG 2019-04-01
シリーズ:	Energies
主題:	renewable energy terminal power consumption energy forecasting grey theory empirical mode decomposition bacterial foraging algorithm extreme learning machine algorithm
オンライン･アクセス:	https://www.mdpi.com/1996-1073/12/7/1331

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