Short-Term Power Demand Forecasting Using Information Technology Based Data Mining Method

机译：基于信息技术的数据挖掘方法在短期电力需求预测中的应用

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This paper proposes information technology based data mining to forecast short term power demand. A time-series analyses have been applied to power demand forecasting, but this method needs not only heavy computational calculation but also large amount of coefficient data. Therefore, it is hard to analyze data in fast way. To overcome time consuming process, the author take advantage of universally easily available information technology based data-mining technique to analyze patterns of days and special days(holidays, etc.). This technique consists of two steps, one is constructing decision tree, the other is estimating and forecasting power flow using decision tree analysis. To validate the efficiency, the author compares the estimated demand with real demand from the Korea Power Exchange.

机译：本文提出了一种基于信息技术的数据挖掘技术来预测短期电力需求。时间序列分析已应用于电力需求预测，但是该方法不仅需要大量的计算，而且需要大量的系数数据。因此，很难快速分析数据。为了克服耗时的过程，作者利用了基于通用信息技术的数据挖掘技术来分析日和特殊日（节假日等）的模式。该技术包括两个步骤，一个是构建决策树，另一个是使用决策树分析估计和预测潮流。为了验证效率，作者将估计的需求与大韩电力交易所的实际需求进行了比较。

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来源
《International Conference on Computational Science and Its Applications(ICCSA 2006) pt.5; 20060508-11; Glasgow(GB)》|2006年|P.322-330|共9页
会议地点 Glasgow(GB)
作者
Sang-Yule Choi;
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作者单位

Dept.of Electronic Engineering , Induk Institute of Technology, San 76 Wolgye-dong, Seoul, South Korea;

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原文格式 PDF
正文语种 eng
中图分类计算技术、计算机技术;
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Short-Term Power Demand Forecasting Using Information Technology Based Data Mining Method

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