热带气象学报2017，Vol.33Issue(1)：104-110,7.DOI:10.16032/j.issn.1004-4965.2017.01.011
基于近似支持向量机的能见度释用预报研究
VISIBILITY FORECAST BASED ON PROXIMAL SUPPORT VECTOR MACHINE
摘要
Abstract
Based on Ts11L61 numerical prediction products and observed stations data of December and January from 2008 to 2010,a classification-regression forecast model is established for visibility at Nanjing,Hangzhou and Quzhou stations by using proximal support vector machine.The model is tested using independent samples of December and January in 2011,and compared with the regression one.The results indicate that the forecasting effect of the classification-regression model is better than that of the regression one.The average accuracy of classification-regression model for the three stations in 24 h,36 h,48 h,60 h and 72 h is 75.5％,83.7％,72.1％,75.4％ and 78.0％,respectively.Its average accuracy is also higher than that of regression one.The classification-regression model is suitable for forecasting visibility at these stations.关键词
近似支持向量机/分类和回归结合的模型/能见度/预报Key words
proximal support vector machine/classification-regression model/visibility/forecast分类
天文与地球科学引用本文复制引用
吴波,胡邦辉,王学忠,黄泓,王举..基于近似支持向量机的能见度释用预报研究[J].热带气象学报,2017,33(1):104-110,7.基金项目
国家自然科学基金(41475070、41330420)共同资助 （41475070、41330420）
