Open AccessUpdated Moving Forecasting Model of Air Maximum Temperature
Author(s) -
Khalid Hashim,
Hussein Al-Bugharbee,
Salah L. Zubaidi,
Nabeel Saleem Saad Al-Bdairi,
Sabeeh Lafta Farhan,
Saleem Ethaib
Publication year - 2021
Publication title -
iop conference series. earth and environmental science
Language(s) - English
Resource type - Journals
eISSN - 1755-1307
pISSN - 1755-1315
DOI - 10.1088/1755-1315/877/1/012032
Subject(s) - air temperature , current (fluid) , series (stratigraphy) , sample (material) , time series , meteorology , work (physics) , moving average , maximum temperature , econometrics , environmental science , computer science , statistics , mathematics , engineering , geography , atmospheric sciences , thermodynamics , physics , mechanical engineering , paleontology , biology
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.