Analysis and predicting electricity energy consumption using data mining techniques — A case study I.R. Iran — Mazandaran province

Noorollah Karimtabar, Sadegh Pasban, S. Alipour
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引用次数: 12

Abstract

The electricity consumption forecast is especially important with regard to policy making in developing countries. In this paper, the electricity consumption rate is predicted using the data mining techniques. The datasets that were collected for predicting the electricity consumption are related to Islamic Republic of Iran - Mazandaran province pertaining to the years 1991 to 2013. The research objective is analyzing the electricity consumption rate in recent years and predicting future consumption. According to a study the electricity consumption growth rate between the years 2006 to 2013 and the years 1999 to 2006 equaled 28.41 and 73.53, respectively. The results of the research conducted using the regression model indicate a 2.48 relative error. The output of this prediction shows that the total electricity consumption rate increases about 3.2% annually on average and will reach 7076796 megawatts by the year 2020 that shows a 22.28% growth comparing to the year 2013.
使用数据挖掘技术分析和预测电力能源消耗-以伊朗马赞达兰省为例
电力消费预测对发展中国家的政策制定尤其重要。本文采用数据挖掘技术对电力消耗率进行预测。为预测电力消耗而收集的数据集与1991年至2013年伊朗伊斯兰共和国马赞达兰省有关。研究的目的是分析近年来的用电量,预测未来的用电量。根据一项研究,2006年至2013年和1999年至2006年的用电量增长率分别为28.41和73.53。使用回归模型进行的研究结果表明,相对误差为2.48。这一预测的输出表明,总用电量平均每年增长3.2%左右,到2020年将达到7076796兆瓦,比2013年增长22.28%。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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