安徽农业大学学报2012，Vol.39Issue(5)：837-842,6.
基于季节ARIMA模型的铜陵市气温序列的预报
Prediction of temperature time series of Tongling city based on season ARIMA model
摘要
Abstract
In this article, we analyzed the time series data of month mean temperature in Tongling city using EVIEWS software, and got modeling prediction according to the dynamical data. We preprocessed the sample data using difference method, and then made sure the model order and estimated the parameter values for establishing the season autoregressive integrated moving average (ARIMA) model to fit the time series. The prediction results showed that the average absolute error of the season ARIMA model is 0.875. Comparing the result of ARIMA model and RBF (radial basis function) neural network, the season ARIMA model is better than radial basis function (RBF ) neural network.关键词
时间序列/ARIMA模型/月平均气温/铜陵市Key words
time series/ ARIMA model/ month mean temperature/ Tongling city分类
天文与地球科学引用本文复制引用
沈艳,张庆国,叶静芸..基于季节ARIMA模型的铜陵市气温序列的预报[J].安徽农业大学学报,2012,39(5):837-842,6.基金项目
国家自然科学基金项目(70271062,40771117)和安徽省级重点科研基金项目(KJ2010A121)共同资助. （70271062,40771117）
