Estimation of climatological parameters using ANN and WEKA models in Diyala Governorate, Iraq

Authors

  • DHER I. BAKR Department of Petroleum Geology and Mineral, College of Sciences, University of Diyala, Diyala, Iraq
  • JASIM Al-KHALIDI Department of Physics, College of Sciences, University of Diyala, Diyala, Iraq
  • HAZIM NOMAN ABED Department of Computer, College of Sciences, University of Diyala, Diyala, Iraq

DOI:

https://doi.org/10.54386/jam.v27i2.2877

Keywords:

WEKA, ANN, Climatic parameters, Temperature, , Humidity, Wind speed

Abstract

Artificial Neural Networks (ANN) and Waikato Environment for Knowledge Analysis (WEKA) model were used to estimate the climatic parameters viz. minimum temperature (Tmin), maximum temperature (Tmax), relative humidity (RH), wind velocity (WV) using the time series of monthly data for the period of 1980 to 2022. It was found that the estimation of the climate parameters using the two methods (WEKA and ANN) obtained acceptable values of correlation (R2) and error standards (RMSE and MAE) between the observed and estimated values, but they differed in accuracy. The WEKA method obtained better values in the estimation of the Tmin component than ANN while the estimation of the Tmax, RH, WV, the ANN method was better than the WEAK model in the estimation of the parameters.

References

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Published

01-06-2025

How to Cite

BAKR, D. I., Al-KHALIDI, J., & ABED, H. N. (2025). Estimation of climatological parameters using ANN and WEKA models in Diyala Governorate, Iraq. Journal of Agrometeorology, 27(2), 210–215. https://doi.org/10.54386/jam.v27i2.2877

Issue

Vol. 27 No. 2 (2025): June

Section

Research Paper

Categories

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Copyright (c) 2025 DHER I. BAKR, JASIM Al-KHALIDI, HAZIM NOMAN ABED

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