Prediction of temperature time series of Tongling city based on season ARIMA model
In this article,we analyzed the time series data of month mean temperature in Tongling city us-ing 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 estab-lishing 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.