The Cost Estimating Model for Façade System of High-Rise Building in the Concept Phase by Using CBR Method

The facade’s value holds significant importance in construction estimates. Typically, it constitutes around 20–25% of the total construction cost for a project. However, this percentage can vary depending on various factors, including the type of work, project size, construction site, material quality, construction items, and the complexity of the project. Therefore, achieving a reasonably accurate cost estimation for the facade value in construction estimates is crucial, particularly when based on the concept drawing. However, predicting these costs is challenging due to the multitude of interactions among various variables. To tackle this issue, Machine Learning (ML) techniques are being explored. This paper aims to present a cost estimation of the facade system for high-rise buildings by constructing a database using a Case-Based Reasoning (CBR) model. Additionally, Solver in excel software is employed to determine the optimal weights in the CBR model, enhancing the accuracy of cost estimation. By leveraging ML and the excel tool, this method offers valuable insights for making informed decisions during construction planning and design.