基于ARIMA神经网络的工业生产指数仿真研究

Simulation Research of Industrial Production Index Based on Neural Network of ARIMA

工业生产指数是衡量某个时期工业经济景气状况和发展趋势的重要指标,也是研究宏观经济预警的首选指标。将ARIMA理论与神经网络理论相结合,构建了ARIMA神经网络模型,采用1997-2015年月度工业生产指数的时间序列数据,开展了工业生产指数的仿真研究。首先对工业生产指数进行季节调整,剔除了工业生产指数时间序列中的季节因素影响;其次通过ARIMA神经网络模型对1997-2015年月度工业生产指数进行仿真,结果表明模型仿真训练效果较好;最后运用ARIMA神经网络模型对2016年1-6月工业生产指数进行模拟仿真,得出了2016年1-6月工业生产指数模拟仿真值。

Industrial production index is an important indicator to measure the status of industrial economic sentiment over a given period of time,and it is also the first indicator for researching the macroeconomic early-warning.In this paper,the ARIMA neural network model was built,through the ARIMA theory combined with neural network theory,and using 1997-2015 monthly time series data of the industrial production index,the simulation research of the industrial production index was carried out.First of all,the seasonal adjustment for industrial production index was made to get rid of the seasonal factors of industrial production index in the time series.Secondly,the 1997-2015 monthly industrial production index by ARIMA neural network model was emulated.The simulation results show a good simulation training effect.Finally,ARIMA neural network model was used to carry on the simulation of the industrial production index from January to June in 2016,and the simulation values of industrial production index from January to June in 2016 was got.