Predicting the Volatility of Highway Construction Cost Index Using Long Short-Term Memory

Author:

Cao Yang1,Ashuri Baabak2

Affiliation:

1. Graduate Research Assistant, School of Building Construction, Georgia Institute of Technology, 280 Ferst Dr., Atlanta, GA 30332-0680.

2. Associate Professor and Brook Byers Institute for Sustainable Systems Fellow, Director of the Economics of Sustainable Built Environment Lab, School of Building Construction and School of Civil and Environmental Engineering, Georgia Institute of Technology, 280 Ferst Dr., Atlanta, GA 30332-0680 (corresponding author).

Publisher

American Society of Civil Engineers (ASCE)

Subject

Management Science and Operations Research,Strategy and Management,General Engineering,Industrial relations

Reference33 articles.

1. Empirical Investigation of Temporal Association between Architecture Billings Index and Construction Spending Using Time-Series Methods

2. Ashuri B. and J. Lu. 2010a. “Exponential smoothing time series models for forecasting ENR construction cost index.” Accessed November 11 2019. http://ascpro0.ascweb.org/archives/cd/2010/paper/CPRT182002010.pdf.

3. Time Series Analysis of ENR Construction Cost Index

4. Ashuri B. S. M. Shahandashti and J. Lu. 2012. “Is the information available from historical time series data on economic energy and construction market variables useful to explain variations in ENR construction cost index?” In Proc. 2012 Construction Research Congress. Reston VA: ASCE.

5. Baek M. 2018. “Quantitative analysis for modeling uncertainty in construction costs of transportation projects with external factors.” Ph.D. thesis School of Building Construction Georgia Institute of Technology.

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