A Review on Feasible Cost Prediction Model in Construction Projects

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N.P.Srinivasan, et. al.


This paper proceeded with the decision-making within the early stages of a construction project which can have a major impact on the project. Restricted and unsure data makes it troublesome to accurately predict construction prices. The advanced cosmic microwave background model can be developed to integrate the benefits of prediction methodologies like cosmic microwave background, Multivariate Regression Analysis (MRA) and Artificial Neural Networks (ANN). An improved method of employing a genetic algorithmic rule is needed to predict the cost fluctuations on the industry. This study outlined four improvement factors, as: minimum threshold for rating the attribute similarity, attribute weight factors, case choice fators and tolerance factor between models. As the model was carried out as victimization, the MS-Excel based platform, Visual Basic Application (VBA) is implemented for easy handling, thus it can be presumed that the idea supports the stakeholders thought of predicting and managing a construction price within the early stages of a construction projects by incorporating results studied from historical cases as references. From previous studies, we've studied the average of construction material prices, which can be incorporated in formulating the prototype.


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