Predicting Conceptual Cost for Field Canal Improvement Projects
Publication: Journal of Construction Engineering and Management
Volume 144, Issue 11
Abstract
A conceptual cost estimation is prepared to assess the feasibility of a project or establish the project’s initial budget at the early stages of the project. The main objective of the paper is automating the cost estimate at the conceptual stage with the highest accuracy. The key contribution of this paper is developing a quadratic regression model with a prediction accuracy of 9.12% and 7.82% for training and validation, respectively. This research has identified the model’s key parameters to establish a reliable conceptual cost estimate model for field canal improvement projects (FCIPs). Two machine learning models were developed utilizing multiple regression analysis (MRA) and artificial neural networks (ANNs). Searching for a better model, several data transformations have been conducted to improve the model performance. The quadratic regression model has shown the highest performance based on the correlation and the mean absolute percentage error (MAPE) criteria. A parametric model has been presented in this paper to predict the conceptual cost of FCIPs. This research maintains the importance of identifying key parameters and conducting data transformation and sensitivity analysis for developing a reliable parametric cost prediction model.
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Data Availability Statement
Data generated or analyzed during the study are available from the corresponding author by request. Information about the Journal’s data-sharing policy can be found here: http://ascelibrary.org/doi/10.1061/(ASCE)CO.1943-7862.0001263.
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Information & Authors
Information
Published In
Journal of Construction Engineering and Management
Volume 144 • Issue 11 • November 2018
Copyright
©2018 American Society of Civil Engineers.
History
Received: Dec 26, 2017
Accepted: May 15, 2018
Published online: Aug 31, 2018
Published in print: Nov 1, 2018
Discussion open until: Jan 31, 2019
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