| 决策树在短期电力负荷预测中的应用 |
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| 引用本文： | 葛宏伟,杨镜非. 决策树在短期电力负荷预测中的应用[J]. 华中电力, 2009, 22(1): 15-18 |
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| 作者姓名： | 葛宏伟 杨镜非 |
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| 作者单位： | 1. 浙江台州电业局变电工区,浙江台州,317000
2. 上海交通大学电气工程系,上海,200030 |
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| 摘 要： | 提出用C45决策树方法解决负荷预测的样本多样性问题。并进行短期负荷预测。通过计算信息增益找出决策树的最佳生成方案，对连续属性计算其熵值找出最佳分段点进行离散化，阐述了规则的生成及其在短期电力负荷预测中的应用方法，算例结果表明，计算精度较高。
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| 关 键 词： | 决策树 负荷预测 熵 信息增益 离散化 数据挖掘 |
Application of Decision Tree on Short-Term Load Forecasting |
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| GE Hong-wei,YANG Jing-fei. Application of Decision Tree on Short-Term Load Forecasting[J]. Central China Electric Power, 2009, 22(1): 15-18 |
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| Authors: | GE Hong-wei YANG Jing-fei |
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| Affiliation: | 1.Zhejiang Province Taizhou Electric Power Bureau Transformer Substation;Taizhou 317000;China;2.Department of Electrical Engineering;Shanghai Jiaotong University;Shanghai 200030;China |
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| Abstract: | This paper presents the decision tree method to forecast the electrical load with diverse samples.Entropy and information gain is calculated to get the best decision tree.Entropy is also used to disperse continuous data attributes and get the best splitting point.The paper describes the way of generating decision tree rules which is applied to short-term load forecasting.Calculation result by the method on a real power grid is highly precise,which proves the applicability of the presented method. |
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| Keywords: | decision tree load forecasting entropy information gain decision tree dispersion data mining |
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