The success of a project is obtained through the proper management from the beginning to the end of the project. Several studies have been conducted in the project management field further to improve the earned value management methodology to forecast the project cost estimate at completion. However, this study provides to investigate a new research methodology proposed to provide more reliable CEAC by using MATLAB R2014a and Multiple regressions. Thus, the main objective of this study is to focus on the development of a cost prediction model for improving cost estimate at completion of building construction projects using MATLAB R2014a, and regression model. The study is conducted on an EVM data set comprising five real-life projects database gathering between 2021 and 2024. The analysis method was made by using Microsoft excel, MATLAB R2014a, and a statistical package for social science as an analysis tool. The finding of the study revealed that the dependability of EAC on input variable produced by the membership function, and rule viewer is 70% of the estimate at compilation which is quite an acceptable value. It was also found that the regression model shows excellent results in prediction with a coefficient of correlation is 95.70%, 99.90%, 96.10%, 92.40%, and 90.40% for the five projects. Similarly, the coefficient of determination is 91.70%, 99.99%, 92.40%, 85.40%, and 81.70% respectively for the five projects. Finally, it can be recommended that the developed model be conducted in building projects to demonstrate its practicality.
Ayalew et al. (Mon,) studied this question.
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