Cost Overrun Analysis Using Artificial Neural Network in Residential Construction Projects

EasyChair Preprint no. 11883

Abstract

This study delves into the analysis of cost overruns in residential construction projects using Artificial Neural Networks (ANN). By incorporating factors identified through a stakeholder and expert-rated survey, the research aims to develop a predictive model. The model utilizes project-specific combinations of these factors to predict cost overruns. Conducted in the context of Mumbai, this research contributes to the construction industry by offering an advanced tool for proactive cost management. The ANN model's adaptability and learning capabilities from historical data hold promise for improving accuracy in forecasting, enabling project managers to implement effective mitigation strategies. This study underscores the potential impact on project  managers to implement effective mitigation strategies. This study underscores the potential impact on project outcomes and the overall enhancement of cost management practices within the residential construction sector.

Keyphrases: Artificial Neural Network, Cost overrun, Predictive Modelling, Residential Construction Projects

@Booklet{EasyChair:11883,
  author = {Ankita Yadav and Jaydeep Pipaliya},
  title = {Cost Overrun Analysis Using Artificial Neural Network in Residential Construction Projects},
  howpublished = {EasyChair Preprint no. 11883},

  year = {EasyChair, 2024}}