Computer Science ›› 2020, Vol. 47 ›› Issue (11A): 531-534.doi: 10.11896/jsjkx.200300099

• Big Data & Data Science • Previous Articles     Next Articles

Using ARIMA Model to Predict Green Area of Park

YAN Xiang-xiang   

  1. School of Statistics,University of International Business and Economics,Beijing 100029,China
  • Online:2020-11-15 Published:2020-11-17
  • About author:YAN Xiang-xiang,born in 1989,bachelor.He is a participant of the Advanced Course for In-service Staff.His main research interests include big data analysis and application.

Abstract: Using ARIMA model in time series is one of the common analysis and prediction methods.In order to predict the green area of the park,in the case where the advantages of other prediction models are not obvious,the ARIMA model is finally selected as the prediction method.The data of landscaping and forestry in Beijing from 1978 to 2017 are surveyed and collected.In the SPSS system,through the steps of data selection,descriptive statistical analysis,autocorrelation graph stationarity test,data stationarity processing,model test,etc.,the ARIMA model suitable for data collection is finally determined,and to predict the green area of the park.Experimental results such as visualization and model statistics show that the model fits and predicts well.

Key words: ARIMA, Prediction, SPSS, Stationarity test, Time series model

CLC Number: 

  • O211.61
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