| 安徽省某地区中长期电力负荷预测 |
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| 引用本文： | 王军.安徽省某地区中长期电力负荷预测[J].吉首大学学报(自然科学版),2018,39(6):46. |
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| 作者姓名： | 王军 |
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| 作者单位： | （安徽工程大学，安徽 芜湖 241000） |
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| 基金项目： | 安徽省高等教育提升计划省级自然科学研究项目（TSKJ2014B04） |
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| 摘 要： | 以安徽省某地区2007-2014年用电量数据作为训练测试样本，采用灰色预测法、人工神经网络预测法和基于人工神经网络的最小二乘支持向量机（LSSVM）预测法计算其均方误差，结果表明，用基于人工神经网络的LSSVM预测法计算出的均方误差整体上比其他2种预测法要小.选用基于人工神经网络的LSSVM预测法对该地区2015-2017年的用电量进行预测，预测数据与实际数据基本接近.
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| 关 键 词： | 电力负荷 预测 中长期 人工神经网络 最小二乘支持向量机 |
Medium and Long Term Power Load Prediction in an Area of Anhui Province |
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| WANG Jun.Medium and Long Term Power Load Prediction in an Area of Anhui Province[J].Journal of Jishou University(Natural Science Edition),2018,39(6):46. |
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| Authors: | WANG Jun |
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| Institution: | (Anhui Polytechnic University,Wuhu 241000,Anhui China) |
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| Abstract: | With the electricity consumption data in 2007-2014 as the training test sample,the mean square errors by the gray prediction method,the artificial neural network prediction method,and the least squares support vector machine (LSSVM) prediction method based on neural network are compared and analyzed.The results show that the a neural network-based LSSVM method has the minimal error,and the prediction of the electricity consumption in an area of Anhui province from 2015 to 2017 is close to the actual electricity consumption. |
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| Keywords: | power load prediction medium and long term artificial neural networks least squares support vector machine |
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