Analysis and Prediction of Dingxi Weather Data Based on ARIMA Model
Due to the significant impact of weather on agricultural production,water resource management,and natural disaster prevention,it adopts the ARIMA model to achieve effective weather prediction.By using ACF and PACF diagrams to roughly determine the parameters of the ARIMA model,the optimal model is ultimately determined.ARIMA(1,1,1)is the daily minimum temperature model,with the residual sequence autocorrelation function and partial autocorrelation function basically falling within the 95%confidence interval.At the same time,the statistical results of Ljung-Box Q indicate that there is no correlation between residuals(P＞0.05),indicating that residuals are white noise and satisfy the assumption of randomness.The final calculation errors(daily minimum temperature)RMSE,MAPE,and MAE are 2.63,1.22%,and 2.06,respectively.The prediction results are good,providing a feasible solution for predicting the weather in Dingxi.
weather forecastingtime series interpolation methodARIMA model
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