Utilizing Artificial Neural Networks to Compare Construction Cost Estimates

Utilizing Artificial Neural Networks to Compare Construction Cost Estimates
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Utilizing Artificial Neural Networks to Compare Construction Cost Estimates
For project feasibility studies and successful completion, reliable construction cost estimates must be made early. A vast array of variables influences the cost estimate. This paper provides a comparison of artificial neural networks (ANN), support vector machines (SVM), and regression analysis (RA) (Perez et al., 2019). This research aims to develop a neural network-based, multilayer perceptron-based model for predicting building costs. Critical phases for project owners, estimators, and contractors are assessing construction costs and predicting price increases. The pricing procedure is challenging because building costs fluctuate frequently and tend to increase over time. The construction cost index has frequently been utilized in project cost estimates.