| 基于回归分析与神经网络的短期负荷预测 |
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| 引用本文： | 王黎明,王艳松,魏志远.基于回归分析与神经网络的短期负荷预测[J].电气应用,2007,26(11):37-39. |
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| 作者姓名： | 王黎明 王艳松 魏志远 |
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| 作者单位： | 1. 中国石油大学信息与控制工程学院,257061
2. 华北油田采油五厂,052360 |
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| 摘 要： | 针对电力系统短期负荷预测中神经网络输入变量选择与网络训练问题,提出了一种基于回归分析与神经网络相结合的短期负荷预测方法,利用回归分析选择神经网络的输入变量,利用遗传算法训练神经网络.实例研究结果表明该方法可以取得较高的预测精度.
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| 关 键 词： | 短期负荷预测 回归分析 RBF网络 遗传算法 |
| 修稿时间： | 2007年1月15日 |
Short-Term Load Forecasting Algorithm Based on Regression Analysis and the Combination of Genetic Algorithm and Neural Network |
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| Wang Liming.Short-Term Load Forecasting Algorithm Based on Regression Analysis and the Combination of Genetic Algorithm and Neural Network[J].Electrotechnical Application,2007,26(11):37-39. |
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| Authors: | Wang Liming |
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| Affiliation: | China University of Petroleum |
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| Abstract: | In allusion to the input variables choice and training of artificial neural network in short-term load forecasting of electrical power system,a short-term load forecasting algorithm based on regression analysis and neural network is presented.Input variables of neural network is selected by regression analysis and training neural network is trained by genetic algorithm.The result of study indicates that this method can gain a higher forecasting precision. |
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| Keywords: | short-term load forecasting regression analysis RBF network genetic algorithm |
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