| 基于遗传算法优化支持向量回归机的网格负载预测模型 |
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| 引用本文： | 唐阔,胡国圣,车喜龙,胡亮.基于遗传算法优化支持向量回归机的网格负载预测模型[J].吉林大学学报(理学版),2010,48(2):251-255. |
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| 作者姓名： | 唐阔 胡国圣 车喜龙 胡亮 |
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| 作者单位： | 吉林大学 计算机科学与技术学院, 长春 130012 |
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| 基金项目： | 国家自然科学基金(批准号:60873235;60473099);;吉林省科技发展计划重大项目基金(批准号:20080318);;教育部新世纪优秀人才项目基金(批准号:NCET-06-0300) |
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| 摘 要： | 提出一种基于遗传算法优化支持向量回归机的模型进行网格负载预测,使用遗传算法和交叉验证技术解决了支持向量回归机参数难以确定的问题.标准数据集仿真实验结果表明,该模型与试验法定参的支持向量回归机和BP神经网络相比具有更优的预测性能.
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| 关 键 词： | 网格负载预测 支持向量回归 遗传算法 |
| 收稿时间： | 2009-03-10 |
Grid Host Load Prediction Model of Support Vector Regression Optimized by Genetic Algorithm |
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| TANG Kuo,HU Guo-sheng,CHE Xi-long,HU Liang.Grid Host Load Prediction Model of Support Vector Regression Optimized by Genetic Algorithm[J].Journal of Jilin University: Sci Ed,2010,48(2):251-255. |
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| Authors: | TANG Kuo HU Guo-sheng CHE Xi-long HU Liang |
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| Institution: | College of Computer Science and Technology, Jilin University, Changchun 130012, China |
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| Abstract: | A support vector regression optimized by genetic algorithm model was developed for grid host load prediction.Genetic algorithm and cross validation technology were applied to solve parameter optimization of support vector regression.Simulation experiments were performed on benchmark data set.Experimental results indicate that the proposed model exhibits better performance than support vector regression model with parameters selected by trial-and-error method and the back-propagation neural network. |
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| Keywords: | grid host load prediction support vector regression genetic algorithm |
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