计算机应用研究2014，Vol.31Issue(3)：692-695,4.DOI:10.3969/j.issn.1001-3695.2014.03.012
旅游客流量预测：基于季节调整的PSO-SVR模型研究
Study on tourism flow forecast: based on seasonal adjustment’ PSO-SVR model
摘要
Abstract
Tourist industry has a strong seasonal trend. Taking seasonal adjustment method for preprocessing of sample data to eliminate the seasonal influence can improve the accuracy of tourism flow prediction. At the same time， SVR is a good machine learning meth关键词
旅游客流量预测/粒子群算法/支持向量回归机/季节调整/均方差比较Key words
tourism flow forecast/particle swarm optimization(PSO)/support vector regression(SVR)/seasonal adjustment/comparison of mean square error分类
管理科学引用本文复制引用
WENG Gang-min,LI Ling-yan..旅游客流量预测：基于季节调整的PSO-SVR模型研究[J].计算机应用研究,2014,31(3):692-695,4.基金项目
国家社会科学基金资助项目(09BJY087) （09BJY087）
河北省社会科学基金资助项目(HB12YJ075) （HB12YJ075）
