Updated Moving Forecasting Model of Air Maximum Temperature. Issue 1 (November 2021)

• Record Type: Journal Article
• Authors: Hashim, Khalid; Al-Bugharbee, Hussein; Zubaidi, Salah L.; Saad Al-Bdairi, Nabeel Saleem; Farhan, Sabeeh L.; Ethaib, Saleem
• Is Part Of: IOP conference series. Volume 877:Issue 1(2021)
• Publication Date: 2021-11
• Subjects: Autoregressive Model -- Baghdad City -- prediction model -- temperature; Earth sciences -- Periodicals; Environmental sciences -- Congresses; Environmental sciences -- Periodicals; 550.5
• DOI: 10.1088/1755-1315/877/1/012032
• Languages: English
• ISSNs: 1755-1307

Abstract

Abstract: In the current study, a moving forecasting model is used for the purpose of forecasting maximum air temperature. A number of recordings are used for building the AR model and next, to forecasting some temperature values ahead. Then the AR model coefficients are updating due to shifting the training sample by adding new temperature values in order to involve the change in temperature time series behaviour. The current work shows a high performance all over the temperature time series, which considered in the analysis.