计算机工程与应用2016，Vol.52Issue(1)：146-150,5.DOI:10.3778/j.issn.1002-8331.1401-0234
基于ARIMA与SVM的国际铀资源价格预测
Uranium resource price forecasting based on ARIMA and SVM model
摘要
Abstract
The traditional model can not capture uranium resource price's comprehensive trend,because of unsteady and nonlinear time-series data.The forecasting model based on the combination of Autoregressive Integrated Moving Average (ARIMA)and Support Vector Machine(SVM)is built to improve the prediction accuracy of the model in this paper and PSO algorithm is used to optimize the parameters of SVM.The proposed model is applied to uranium resource price tendency forecasting example,and the simulation results show that the forecasting performance of the hybrid model outperforms single ARIMA and SVM ahead forecasting.关键词
差分自回归移动平均/支持向量机/组合预测/国际铀资源价格Key words
Autoregressive Integrated Moving Average(ARIMA)/Support Vector Machine(SVM)/combination forecasting/uranium resource price分类
信息技术与安全科学引用本文复制引用
郑荣,颜七笙..基于ARIMA与SVM的国际铀资源价格预测[J].计算机工程与应用,2016,52(1):146-150,5.基金项目
江西省自然科学基金(No.20114BAB201022) （No.20114BAB201022）
江西省高校人文社科研究项目(No.GL1202) （No.GL1202）
东华理工大学研究生创新基金(No.DHYC2014017). （No.DHYC2014017）
