NDLI: Beijing-Tianjin-Hebei Energy Demand Combination Forecast Analysis

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Beijing-Tianjin-Hebei Energy Demand Combination Forecast Analysis

Content Provider	Scilit
Author	Li, Jian Zhang, Xiaoqian
Copyright Year	2021
Description	Journal: Iop Conference Series: Earth and Environmental Science Energy demand forecasting is the basis for responding to high-quality economic development requirements and targeted adjustments to the Beijing-Tianjin- Hebei energy structure. This paper selects five main factors that affect energy demand, constructs a combined forecasting model of a combination of multi-factor gray neural network and ARIMA-BP neural network, and introduces the idea of chaos optimization on this basis to simulate and analyse data from 2012 to 2016, and predict the energy demand in the Beijing-Tianjin-Hebei region in 2020 and 2025.The results show that: 1. Compared with the CGA-ARIMA-BP model and the CGA-GNN model, the CGA-GNN-ARIMA-BP model has higher prediction accuracy; 2. It is estimated that in 2020 and 2025, the energy demand in the Beijing-Tianjin-Hebei region will reach 493 and 552 million tons of standard coal.
Related Links	https://iopscience.iop.org/article/10.1088/1755-1315/631/1/012104/pdf
ISSN	17551307
e-ISSN	17551315
DOI	10.1088/1755-1315/631/1/012104
Journal	Iop Conference Series: Earth and Environmental Science
Issue Number	1
Volume Number	631
Language	English
Publisher	IOP Publishing
Publisher Date	2021-01-01
Access Restriction	Open
Subject Keyword	Journal: Iop Conference Series: Earth and Environmental Science Industrial Engineering
Content Type	Text
Resource Type	Article
Subject	Earth and Planetary Sciences Physics and Astronomy Environmental Science

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