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| 基于支持向量机的短期风速预测研究 | |
| 引用本文： | 王慧勤. 基于支持向量机的短期风速预测研究[J]. 宝鸡文理学院学报(自然科学版), 2009, 29(1) |
| 作者姓名： | 王慧勤 |
| 作者单位： | 宝鸡文理学院,数学系,陕西,宝鸡,721013;西安科技大学,理学院,陕西,西安,710054 |
| 基金项目： | 宝鸡文理学院科研项目 |
| 摘 要： | 目的 为了减少风电场风速预测的误差,研究基于支持向量机(SVM)模型的短期风速预测.方法 采用SVM回归估计算法建立预测模型.结果 将该方法应用于实测数据进行预测,结果表明预测误差确实得到了降低.结论 和传统回归方法(如ARMA)比较说明所建模型是可行和有效的. |
| 关 键 词： | 支持向量机 短期风速 预测 |
Forecasting study of short-term wind speed based on SVM |
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| WANG Hui-qin. Forecasting study of short-term wind speed based on SVM[J]. Journal of Baoji College of Arts and Science(Natural Science Edition), 2009, 29(1) | |
| Authors: | WANG Hui-qin |
| Affiliation: | 1.Department of Mathematics;Baoji University of Arts and Sciences;Baoji 721013;Shaanxi;China;2.School of Science;Xi'an University of Science and Technology;Xi'an 710054;China |
| Abstract: | Aim In order to reduce the forecasted error of wind speed on wind farm,a study of the forecasting model of short-term wind speed based on SVM(Support Vector Machine)was made.Methods SVM regression estimate algorithm is applied to building forecasting model.Results The presented method applied to actual wind speed forecasting,the results show that the forecasted errors are decreased really.Conclusion Compared with traditional regression algorithm(such as ARMA),the building model is feasible and effective. |
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