实验科学与技术2023，Vol.21Issue(5)：1-9,9.DOI:10.12179/1672-4550.20220546
改进特征选择的光伏功率预测融合算法
Photovoltaic Power Prediction Fusion Algorithm Based on Improved Feature Selection
摘要
Abstract
To improve the accuracy of photovoltaic power prediction,a fusion prediction model based on improved feature selection was proposed.Firstly,the Pearson correlation coefficient and the information gain method were combined to select characteristic parameters.Then,the dataset was classified to construct the single model of XGBoost,LightGBM and multilayer perceptron(MLP).Finally,a MLP with two hidden layers was used to build a fusion model.The results show that the fusion prediction model has higher prediction accuracy and stronger generalization ability than the single model,and can better meet the needs of short-term photovoltaic power prediction.关键词
特征选择/多层感知器/融合模型/光伏功率预测Key words
feature selection/multilayer perceptron/fusion model/photovoltaic power prediction分类
信息技术与安全科学引用本文复制引用
苏华英,王融融,张俨,廖胜利,王国松,代江..改进特征选择的光伏功率预测融合算法[J].实验科学与技术,2023,21(5):1-9,9.基金项目
国家自然科学联合基金(U1765103). （U1765103）
