| 基于随机森林算法的用电负荷预测研究 |
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| 引用本文： | 李婉华,陈 宏,郭 昆,郭松荣,韩嘉民,陈羽中.基于随机森林算法的用电负荷预测研究[J].计算机工程与应用,2016,52(23):236-243. |
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| 作者姓名： | 李婉华 陈 宏 郭 昆 郭松荣 韩嘉民 陈羽中 |
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| 作者单位： | 1.福州大学 数学与计算机科学学院，福州 350116
2.福建省网络计算与智能信息处理重点实验室，福州 350116
3.国网信通亿力科技有限责任公司，福州 350001 |
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| 摘 要： | 为了解决当下用电负荷预测精度不高，难以很好模拟实际用电负荷的分布情况而不能对未来的负荷数据进行合理预测的问题，实现了基于随机森林的分类模型、回归模型以及结合Weka的时间序列模型，对某省份的负荷数据进行预测，通过对不同模型的大量的实验及评估，发现这三个模型皆能合理地预测未来的用电负荷数据。此外，在同一评估指标下随机森林算法结合WEKA中的时间序列模型的方法能够较好地预测未来时刻的负荷数据。
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| 关 键 词： | 用电负荷预测 随机森林 分类 回归 时间序列 |
Research on electrical load prediction based on random forest algorithm |
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| LI Wanhua,CHEN Hong,GUO Kun,GUO Songrong,HAN Jiamin,CHEN Yuzhong.Research on electrical load prediction based on random forest algorithm[J].Computer Engineering and Applications,2016,52(23):236-243. |
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| Authors: | LI Wanhua CHEN Hong GUO Kun GUO Songrong HAN Jiamin CHEN Yuzhong |
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| Affiliation: | 1.College of Mathematics and Computer Science, Fuzhou University, Fuzhou 350116, China
2.Fujian Provincial Key Laboratory of Network Computing and Intelligent Information Processing, Fuzhou 350116, China
3.State Grid Electric Power Company, Fuzhou 350001, China |
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| Abstract: | In order to improve the accuracy of electricity load prediction and solve the problem of simulating the actual distribution of electricity load, it implements the classification model, regression model and time series model of combining the Weka which are based on random forest to forecast the electricity load data of a certain province. After a large number of experiments and evaluation on different models, it finds that the three models can reasonably predict the future of electricity load data. In addition, under the same evaluation index the model which combines the random forest algorithm and time series of WEKA can get better result when predicting the future moment of electricity load data. |
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| Keywords: | electrical load prediction random forest classification regression time series |
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