Abstract: In order to establish the forecasting model of SaaS（Software as a Service） operation, the combined forecasting model based on principal component analysis is proposed, and is applied in the forecasting of SaaS operation. A novel combined forecasting model based on principal component analysis is established, which uses three different forecasting models—phase space reconstruction model, grey model, cubic exponential smoothing model. The simulation results show that the combined forecasting model based on principal component analysis, which takes advantages of the unique strength of each model, can provide more precise forecasting than that of each individual model. This combined forecasting model is demonstrated to be efficient for the forecasting of SaaS operation.

Key words: phase space reconstruction, grey model, cubic exponential smoothing model, principal component analysis, combined forecasting model

摘要： 为了建立面向SaaS运营的预测模型，提出了一种基于主成分分析的组合预测模型并应用于SaaS运营预测中。利用相空间重构预测模型、灰色预测模型和三次指数平滑预测模型这三种单一预测模型，结合主成分分析策略，建立组合预测模型。仿真实验结果表明，基于主成分分析的组合预测模型的预测精度高于各单一预测模型，发挥了各单一预测模型的优势，是面向SaaS运营预测的一种有效方法。

关键词: 相空间重构, 灰色预测模型, 三次指数平滑预测模型, 主成分分析, 组合预测模型