| 变尺度混沌优化参数的LSSVM短期负荷预测 |
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| 引用本文： | 龙文,徐松金.变尺度混沌优化参数的LSSVM短期负荷预测[J].水电能源科学,2011,29(11):186-188,176. |
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| 作者姓名： | 龙文 徐松金 |
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| 作者单位： | 1. 贵州财经学院贵州省经济系统仿真重点实验室,贵州贵阳,550004
2. 铜仁学院数学与计算机科学系,贵州铜仁,554300 |
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| 基金项目： | 国家自然科学基金资助项目(61074069) |
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| 摘 要： | 为解决短期电力负荷预测中LSSVM模型的参数难以确定的问题，利用变尺度混沌算法优化LSSVM模型的惩罚因子和核函数参数，构建了MSC-LSSVM模型，并将其应用于湖南省隆回县地区电网各小时点的数据分析和预测中。结果表明，MSC-LSSVM模型避免了人为选择参数的盲目性，预测精度较高。
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| 关 键 词： | 最小二乘支持向量机 变尺度混沌算法 短期负荷 预测 优化 |
Short-term Load Forecasting Based on LSSVM with Mutative Scale Chaos Optimization Parameters |
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| LONG Wen,XU Songjin.Short-term Load Forecasting Based on LSSVM with Mutative Scale Chaos Optimization Parameters[J].International Journal Hydroelectric Energy,2011,29(11):186-188,176. |
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| Authors: | LONG Wen XU Songjin |
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| Abstract: | In order to overcome drawbacks of parameters selection of LSSVM model for short-term load forecasting, the mutative scale chaos (MSC) algorithm is developed to optimize two parameters of LSSVM model such as penalty factor and kernel function. And then the MSC-LSSVM model is established to predict each hour load of Longhui City in Hunan Province. The results show that the proposed model avoids the blindness of man-made choice of parameters and has high prediction precision. |
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