西华大学学报（自然科学版）2017，Vol.36Issue(1)：35-38,4.DOI:10.3969/j.issn.1673-159X.2017.01.007
萤火虫算法优化SVR参数在短期电力负荷预测中的应用
Application of Firefly Algorithm-Based Optimization of SVR Parameters in Short-term Power Load Forecasting
唐宏 1冯平 2陈镜伯 1陈杰睿 1朱建疆1
作者信息
- 1. 后勤工程学院机械电气工程系,重庆401311
- 2. 中国人民解放军96213部队,云南 玉溪653100
- 折叠
摘要
Abstract
Because firefly algorithm has such advantages as good global performance and high convergence precision, it is used to optimize the SVR penalty coefficient C and kernel parameterσ. A random disturbance is applied to the position of the brightest firefly in the iterative process to improve the original firefly algorithm, and a higher convergence rate and optimization accuracy are obtained. Optimized parameters are used for a short-term load forecasting to improve the prediction accuracy. This method is used to find the opti-mal parameters and make the regression forecast. Compared with grid search method, genetic algorithm and particle swarm optimization algorithm, the prediction results demonstrate modified firefly algorithm better than other several algorithms for parameter optimization.关键词
萤火虫算法/支持向量机/电力负荷预测Key words
firefly algorithm/support vector machines/power load forecasting分类
信息技术与安全科学引用本文复制引用
唐宏,冯平,陈镜伯,陈杰睿,朱建疆..萤火虫算法优化SVR参数在短期电力负荷预测中的应用[J].西华大学学报（自然科学版）,2017,36(1):35-38,4.
