Review on Cost Overrun Analysis Using Artificial Neural Network in Residential Construction Projects

Abstract

Cost overrun in residential construction projects is a prevalent issue that adversely affects project stakeholders and the construction industry as a whole. The objective of this research is to develop a robust predictive model using Artificial Neural Network to anticipate and mitigate cost overruns in residential construction projects. The anticipated outcomes of this research include the development of an accurate cost overrun prediction tool that can assist project stakeholders in proactively managing and controlling construction budgets. By identifying potential cost overrun risks early in the project lifecycle, decision-makers can make informed choices to mitigate these risks and improve project cost management. The findings of this research may inform industry best practices and contribute to the sustainable and efficient execution of residential construction projects. In conclusion, this research project endeavours to leverage Artificial Neural Networks to address the challenge of cost overrun in residential construction projects, ultimately fostering more reliable and cost-effective project delivery in the construction industry.