Ruiguo Yu1,2, Zhiqiang Liu1,2, Jianrong Wang1,3, Mankun Zhao1,2, Jie Gao1,3, Mei Yu1,3,*
Computer Systems Science and Engineering, Vol.33, No.4, pp. 267-274, 2018, DOI:10.32604/csse.2018.33.267
Abstract The spatio-temporal feature with historical wind power information and spatial information can effectively improve the accuracy of wind power prediction,
but the role of the spatio-temporal feature has not yet been fully discovered. This paper investigates the variance of the spatio-temporal feature. Based on
this, a hybrid machine learning method for wind power prediction is designed. First, the training set is divided into several groups according to the variance
of the input pattern, and then each group is used to train one or more predictors respectively. Multiple machine learning methods, such as the support
vector machine regression and the decision… More >
Login
Register
