Artificial Intelligence and Machine Learning Applications in Construction Cost Forecasting: Model Evaluation and Web-Based Deployment

Estimation of construction costs is considered as very important for effective budgeting, planning, and decision-making in civil infrastructure projects. The widely used traditional methods of construction cost estimation often rely on historical trends of the cost analysis, expert judgment, and manual calculations, the processes which can be time-consuming and prone to human error. This study proposes a machine learning-based approach to automate and enhance the accuracy of construction cost prediction using a multi-output regression framework a comprehensive dataset of 10,000 construction instances was compiled from various sources; it includes parameters such as material types, structural categories, area in square feet, and labour specifications among others.