能源消耗
消费(社会学)
可解释性
竞赛(生物学)
计算机科学
能量(信号处理)
鉴定(生物学)
计量经济学
乘法函数
运筹学
经济
数学
人工智能
工程类
统计
生态学
社会科学
社会学
生物
数学分析
植物
电气工程
作者
Yunxin Zhang,Huan Guo,Ming Sun,Sifeng Liu,Jeffrey Yi‐Lin Forrest
出处
期刊:Energy
[Elsevier BV]
日期:2022-11-23
卷期号:264: 126154-126154
被引量:14
标识
DOI:10.1016/j.energy.2022.126154
摘要
Energy is the foundation for the stable operation and long-term growth of the national economy. Quantifying the degree of competition and cooperation among different types of energy consumption and predicting its future development trend will help to analyze the changes in energy consumption structure, to better formulate and make decisions on energy policies. In view of the inherent complexity of the energy consumption system structure, this paper proposes a novel grey Lotka–Volterra model (GLVM) for energy consumption forecasting, to evaluate the impact of long-term competition and cooperation on the national energy consumption system and its development trend. In theory, the solution method and parameter identification of the GLVM are given, and the parameter characteristics of GLVM under multiplicative transformation are analyzed. Based on this, the GLVM is used to analyze the consumption structure of different types of energy in China, the United States and Germany, and quantitatively analyzes the internal relationship of the energy consumption structure of the three representative countries. Compared with other models, the results show that this model is superior to other existing models in accuracy and interpretability. The model proposed in this paper is of great value to researchers and decision makers.
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