Estimating Annual Maintenance Expenditures for Infrastructure: Artificial Neural Network Approach-Reference-Cited by-同舟云学术

Estimating Annual Maintenance Expenditures for Infrastructure: Artificial Neural Network Approach

Published:2016-06 Issue:2 Volume:22 Page:04015025
ISSN:1076-0342
Container-title:Journal of Infrastructure Systems
language:en
Short-container-title:J. Infrastruct. Syst.

Author:

Woldemariam Wubeshet¹,Murillo-Hoyos Jackeline²,Labi Samuel³

Affiliation:

1. Visiting Assistant Professor, Purdue Univ. Calumet, Powers Building, Room 211, 2200 169th St. Hammond, IN 46323 (corresponding author).

2. Research Assistant, Lyles School of Civil Engineering, Hampton Hall, Purdue Univ., 550 Stadium Mall Dr., West Lafayette, IN 47907; Professor, School of Civil Engineering and Geomatics, Universidad del Valle, Santiago de Cali 760032, Colombia.

3. Associate Professor, Lyles School of Civil Engineering, Purdue Univ., Hampton Hall, 550 Stadium Mall Dr., W. Lafayette, IN 47907.

Publisher

American Society of Civil Engineers (ASCE)

Subject

Civil and Structural Engineering

Link

http://ascelibrary.org/doi/pdf/10.1061/%28ASCE%29IS.1943-555X.0000280

Reference29 articles.

1. Adams T. (2011). “Estimating cost per lane mile for routine highway operations and maintenance.” Rep. No. MRUTC 07-12 Wisconsin Dept. of Transportation Madison WI.

2. Operating and Maintenance Costs of the TGV High‐Speed Rail System

3. Prediction of hourly air pollutant concentrations near urban arterials using artificial neural network approach

4. CBO (Congressional Budget Office). (2011). “Spending and funding for highways.” U.S. Congress Washington DC.

5. Applications of neural networks in transportation

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