ARIMA-RBFNN组合模型在白城市降水量预测中的应用
Application of ARIMA-RBFNN Model in Prediction of Precipitation in Baicheng City
安永凯 1卢文喜 1宋文博 1贺石良 1赵莹1
作者信息
- 1. 吉林大学环境与资源学院,吉林长春130026
- 折叠
摘要
针对降水受大气环流、地形、气压等诸多环境因素影响致使准确预报降水量较为困难的问题,结合ARIMA模型和RBFNN模型各自优势,提出了ARIMA-RBFNN组合模型,对白城市2001～2010年降水量进行了预报,并与ARIMA模型和RBFNN模型预报结果进行了对比分析.结果表明,ARIMA-RBFNN组合模型在预测降水量时最大相对误差为27.33％,最小相对误差为0.70％,平均相对误差为8.54％,预测精度明显优于ARIMA模型和RBFNN模型,可见该组合模型发挥了ARIMA模型和RBFNN模型各自的优点,为精确预测降水量提供了一种有效方法.
Abstract
Precipitation is influenced by atmospheric circulation,topography,air pressure and other environmental factors,so accurate prediction of precipitation is difficult.Combining advantages of ARIMA model and RBFNN model,ARIMA-RBFNN combination model is proposed to predict the precipitation of Baicheng city from 2001 to 2010.Compared with the ARIMA model and RBFNN model,the results show that the maximum relative error of ARIMA-RBFNN model for prediction of precipitation is 27.33％,the minimum relative error is 0.70％,and the average relative error is 8.54％ ; the prediction accuracy is better than that of ARIMA model and RBFNN model.Thus,combination model play the advantages of ARIMA model and RBFNN model respectively,which provides an effective method for prediction of precipitation.
关键词
降水量/ARIMA-RBFNN组合模型/ARIMA模型/RBFNN模型Key words
precipitation/ARIMA-RBFNN combination model/ARIMA model/RBFNN model引用本文复制引用
出版年
2014
NETL
NSTL
维普
万方数据