Combining Cluster Analysis with Multiple Linear Regression Analysis to Create the Most Accurate Prediction Model for Evaporation in the Kurdistan Region of

Section: Research Paper
Issue
Vol. 20 No. 2 (2023): Volume 20 Issue 2
Published
Jun 25, 2025
Pages
188-199

Abstract

This study aims to build a prediction model for the influential variables of evaporation in the Kurdistan region - Iraq, using the concept of regression and cluster analysis. The methods common guide the work to highlight the strengths of each technique, and the possibility of using hierarchical cluster analysis (nearest neighbor, furthest neighbor, and median) to improve the predictive accuracy of regression models. The variables affecting the evaporation rate were classified using weather data from meteorological stations in the Kurdistan Region, Iraq for the period from January 2020 to December 2022, and The adjusted R2, MSE, and RMSE values were used as indicators of the efficiency of the models performance. The study found that clustering before regression analysis leads to improve prediction accuracy by classifying and identifying homogeneous independent variables within one cluster that are different from the rest of the clusters.

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Authors

Bakhshan Ahmed Hamad

Department of Mathematics, College of Education, Salahaddin University, Erbil, Iraq

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How to Cite

Ahmed Hamad, B., & بخشان. (2025). Combining Cluster Analysis with Multiple Linear Regression Analysis to Create the Most Accurate Prediction Model for Evaporation in the Kurdistan Region of. IRAQI JOURNAL OF STATISTICAL SCIENCES, 20(2), 188–199. Retrieved from https://rjps.uomosul.edu.iq/index.php/stats/article/view/20642