中北大学学报（自然科学版）2018，Vol.39Issue(4)：373-379,7.DOI:10.3969/j.issn.1673-3193.2018.04.001
基于MFO-SVM的空气质量指数预测
Prediction of Air Quality Index Based on MFO-SVM
摘要
Abstract
In practical engineering problems,the traditional Moth-flame optimization (MFO)algorithm was easy to converge prematurely and resulted in falling into a local optimum,which made the efficiency of solving practical problems lower.SVM had an advantage in regional optimization of intelligent algo-rithms and MFO was easy to fall into premature convergence.Therefore,the combination of SVM and MFO was proposed,written as MFO-SVM.The Daily Air Quality Indexes (AQI)of Taiyuan and Da-tong in Shanxi were selected to verify the feasibility and effectiveness of MFO-SVM algorithm.The ex-perimental results show that the relative error of the MFO-SVM algorithm is close to zero and the pre-dicted value is closer to the actual value,which can effectively predict the air quality index.关键词
飞蛾扑火优化(MFO)算法/支持向量机(SVM)/空气质量指数预测(AQI)Key words
Moth-flame optimization(MFO)/support vector machines(SVM)/air quality prediction分类
信息技术与安全科学引用本文复制引用
高帅,胡红萍,李洋,白艳萍..基于MFO-SVM的空气质量指数预测[J].中北大学学报（自然科学版）,2018,39(4):373-379,7.基金项目
国家自然科学基金资助项目(61774137) （61774137）
山西省自然科学基金资助项目(201701D22111439) （201701D22111439）
