Propose suitable machine learning algorithms to estimate the quantity of materials for construction projects

Abstract

Conceptual cost models play an important role in the success of a construction project. In this stage, the cost models often do not detail of materials, equipment and personel. This has prevented project managers from proactively planning their resources in the early of project. In particular, the cost of materials often take up a large proportion in the cost structure of civil projects. The previous studies on estimating quantities of materials only focused mainly in the fields of : traffic, plant projects, ... the models for estimating quantities in civil projects were limited and used the software that is relatively inaccessible to stakeholders in the construction industry. By using Weka software, this study will propose suitable machine learning algorithms to build a model to estimate the quantity of materials for civil projects of reinforced concrete structures. The prediction results from the proposed model will be ranked in order to propose suitable algorithms for exploiting concrete, formwork, and reinforcement models for components : foundation, column, beam and floor.