A Chinese New Year Aware ARIMA Model for Electricity Consumption Forecast

被引：0

作者：

Cai, Tiao ^{[1
]}

Wang, Xin ^{[1
]}

Huang, Sui ^{[1
]}

机构：

[1] JiNan Univ, Dept Comp Sci, Guangzhou 510632, Guangdong, Peoples R China

来源：

PROCEEDINGS OF THE 2013 INTERNATIONAL CONFERENCE ON ADVANCED COMPUTER SCIENCE AND ELECTRONICS INFORMATION (ICACSEI 2013) | 2013年 / 41卷

关键词：

consumption forecast; time series; seasonal effect; ARIMA model;

D O I：

暂无

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

The forecast of electricity consumption has a siginificant impact on both economics and society. Various models have been developed to make this forecast accurate. Among them is the highly successful ARIMA model which is based on time series analysis. However, when applied local in China, ARIMA forecast is not as accurate as expected, due to the moving holiday effect of Chinese New Year feastive period. This paper proposes a revised ARIMA model which adjusts its forecast by the use of a China New Year (CNY) coefficient. Preliminary experimental results on real data show that this revised model outperforms the traditional one.

引用

页码：385 / 387

页数：3

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