Utilizing Artificial Neural Networks to Compare Construction Cost Estimates

Research Proposal Instructions:

One paragraph describes the project
One paragraph explains how you will conduct your research (what qualitative and quantitative analyses you'll be incorporating).
One paragraph explains what you will do with the research outcomes and paper in general.
e.g. Select a project that has sufficient data to allow you to do an EVMS analysis on the project.
The proposal is for a ten page research paper.

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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.

Updated on January 26, 2024

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Utilizing Artificial Neural Networks to Compare Construction Cost Estimates

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