能源消耗
消费(社会学)
计算机科学
能量(信号处理)
期限(时间)
计量经济学
生产(经济)
能量平衡
统计
经济
工程类
数学
生态学
社会学
宏观经济学
物理
电气工程
生物
量子力学
社会科学
作者
Lu Peng,Lin Wang,De Xia,Qinglu Gao
出处
期刊:Energy
[Elsevier]
日期:2021-08-12
卷期号:238: 121756-121756
被引量:145
标识
DOI:10.1016/j.energy.2021.121756
摘要
Energy consumption is an important issue of global concern. Accurate energy consumption forecasting can help balance energy demand and energy production. Although there are various energy consumption forecasting methods, the forecasting accuracy still needs to be improved. This study applied a long short-term memory-based model in energy consumption forecasting to achieve a better prediction performance and the more critical influencing factors are emphasized. Results of one comparative example and two extended applications show the proposed model achieves better prediction accuracy compared with basic long short-term memory and other existing popular models. Mean absolute percentage errors of the proposed model for three real-life cases are 4.01 %, 5.37 %, and 1.60 %, respectively. Therefore, the proposed model is a satisfactory method for energy consumption forecasting due to its high accuracy. The high-precision forecasting technology is important for the energy systems.
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