Application of Grey Forecasting Models for Forecasting the Number of Marriages in Halabja Governorate-Iraq

Abstract

Time series forecasting encompasses the examination of historical data to anticipate future values, rely on relevant historical and present data or information for forecasting upcoming values. Thus, gray theory deals with systems with inadequate, poor, and uncertain information. Modeling on insufficient sample and saturation sequences. The objective of this study is to determine the most suitable model from the models proposed (GM (1,1) Model, Discrete Grey Model (DGM) (1,1), Grey Verhulst Model (GVM) (1,1), and Exponential Grey Model (EXGM) (1,1)) for predicting the number of marriages in Halabja governorate, Iraq, in the future. Annual data on the number of marriages from 2016 to 2023 are utilized in this research and Microsoft excel to analyze data. Experimental results indicate that the EXGM (1,1) model is the most accurate model selected in this study, with the lowest average value of MAPE (2.8405%) and a higher level of precision of 97.1595% compared to the other models. This suggests that the EXGM (1,1) model provides more accurate values than the other models. EXGM (1,1) is strongly recommended for forecasting the number of marriages in Halabja governorate, Iraq, for the period 2024-2040.