基于ARIMA-SVM组合模型的移动通信用户数预测

Prediction on the number of mobile subscribers based on combined model ARIMA-SVM

运营商通过分析各时段、各区域的历史移动通信业务数据,能够预测未来一段时间的业务量,从而提供面向管理层的决策支持。为准确把握国内移动通信用户数的波动规律,提高预测精度,通过对2012年1月到2014年2月的26个月忙时移动通信用户总数和3G用户数进行分析,采用差分自回归移动平均模型(ARIMA)对业务量时间序列数据进行线性建模,并采用支持向量机(SVM)对ARIMA模型残差进行非线性建模,将ARIMA模型与SVM模型组合对忙时移动通信用户数进行预测,结果表明,ARIMA-SVM组合模型预测精度明显优于单一模型,发挥了两种模型各自的优势。该组合模型是一种切实可行的移动通信业务预测方法。

In order to forecast the prospective volume of business in the filed of mobile communication and provide decision support to managers, the historical mobile data communications service in every period and region are analyzed. Through investigating the total number of mobile subscribers and 3G users in busy hours from Jan,？2012？to？Feb, 2014, difference autoregressive moving average model（ARIMA） is utilized to carry out a linear modeling for volume of business’ s time-series data.Support vector machine（SVM） is applied to perform nonlinear modeling for residual error of ARIMA model. The number of mobile subscribers in busy hours is predicted by combining ARIMA model with SVM model. The results indicate that the combination ARIMA-SVM includes almost all advantages of its compositions and has a higher prediction accuracy then the single model, ARIMA or SVM. Therefore, combination model is a practical prediction method for mobile communication services.