使用ARIMA模型预测公园绿地面积

doi:10.11896/jsjkx.200300099

摘要/Abstract

摘要： 在时间序列中使用ARIMA模型是常见的分析预测方式之一。为了预测公园绿地面积,在其他预测模型优势不明显的情况下,最终选择ARIMA模型作为预测方法。文中调研并选取了北京市1978－2017年园林绿化及森林情况数据,在SPSS系统中,通过数据选择、描述性统计分析、自相关图平稳性检验、数据平稳性处理、模型检验等步骤最终确定适合采集数据的ARIMA模型,并在该模型上对2018－2020年的公园绿地面积进行预测。可视化和模型统计量等实验结果表明,该模型的拟合及预测效果良好。

关键词: ARIMA, SPSS, 平稳性检验, 时间序列模型, 预测

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

中图分类号:

O211.61

闫祥祥. 使用ARIMA模型预测公园绿地面积[J]. 计算机科学, 2020, 47(11A): 531-534. https://doi.org/10.11896/jsjkx.200300099

YAN Xiang-xiang. Using ARIMA Model to Predict Green Area of Park[J]. Computer Science, 2020, 47(11A): 531-534. https://doi.org/10.11896/jsjkx.200300099

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