Analysis and Modeling for China’s Electricity Demand Forecasting Using a Hybrid Method Based on Multiple Regression and Extreme Learning Machine: A View from Carbon Emission

Analysis and Modeling for China’s Electricity Demand Forecasting Using a Hybrid Method Based on Multiple Regression and Extreme Learning Machine: A View from Carbon Emission

The power industry is the main battlefield of CO2 emission reduction, which plays an important role in the implementation and development of the low carbon economy. The forecasting of electricity demand can provide a scientific basis for the country to formulate a power industry development strategy...

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Bibliographic Details
Main Authors: Yi Liang, Dongxiao Niu, Ye Cao, Wei-Chiang Hong
Format: Article
Language:English
Published: MDPI AG 2016-11-01
Series:Energies
Subjects:
electricity demand forecasting
multiple regression (MR)
extreme learning machine (ELM)
induced ordered weighted harmonic averaging operator (IOWHA)
grey relation degree (GRD)
carbon emission
Online Access:http://www.mdpi.com/1996-1073/9/11/941

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http://www.mdpi.com/1996-1073/9/11/941

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