基于ARIAM和GM(1,1)模型的我国通用航空运营企业数量预测  

Prediction of the Number of Chinese General Aviation Operating Enterprises Based on ARIAM and GM(1,1)Models

作　　者：胡俊涛 余长春[1] HU Juntao;YU Changchun(School of Economics and Management,Nanchang Hangkong University,Nanchang 330063,China)

机构地区：[1]南昌航空大学经济管理学院,江西南昌330063

出　　处：《现代信息科技》2024年第9期136-139,共4页Modern Information Technology

基　　金：江西省省科技厅管理科学项目(20232BAA10041);航空基金(2022Z069056002);江西省哲学社会科学重点研究基地重点项目(22SKJD19)。

摘　　要：作为我国民航两翼之一的通用航空正迅速发展,为全面掌握通航运营企业发展规律,基于2010—2022年的数据分别运用SPSS26、Python 3.9和SPSSPRO建立ARIMA与GM(1,1)两种模型并对我国通航运营企业数量规模预测比较,选择拟合度更佳的模型进行短期预测分析。结果表明:ARIMA(0,2,0)模型和GM(1,1)模型的预测值与实际值拟合度均满足对未来短期数据的预测,但GM(1,1)模型后验差比值为0.001,模型平均相对误差为1.868%,模型不仅精度高,模型拟合效果也好,在预测中更佳。预测结果可为通航发展规划战略提供相应的数据支持。As one of the two wings of Chinese civil aviation,general aviation is developing rapidly.In order to fully grasp the development law of general aviation operation enterprises,this paper uses SPSS26 and Python 3.9 to establish ARIMA and GM(1,1)models based on the data from 2010 to 2022,and compares the number and scale of Chinese general aviation operating enterprises,and selects the model with better fitting for short-term prediction analysis.The results show that the fit between the predicted value and the actual value of the ARIMA(0,2,0)model and the GM(1,1)model both meet the prediction of future short-term data,but the post-posterior difference ratio of the GM(1,1)model is 0.001,and the average relative error of the model is 1.868%,which not only has high accuracy,but also has good model fitting effect and is better in prediction.The prediction results can provide corresponding data support for the general aviation development planning strategy.

关 键 词：通用航空 运营企业数量 ARIMA GM(1 1) 

分 类 号：TP391[自动化与计算机技术—计算机应用技术]