A Multilayer Perceptron-Based Neural Network Model for Predicting Steel Bridge Coating Conditions by Integrating Bridge and Environmental Features

Author:

Rahman Md. Ashiqur1234,Zhang Lu1234,Lau Kingsley1234,Lv Xuan1234

Affiliation:

1. Ph.D. Candidate, Dept. of Civil and Environmental Engineering, Florida International Univ., Miami, FL.

2. Associate Professor, Myers-Lawson School of Construction, Virginia Tech, Blacksburg, VA.

3. Associate Professor, Dept. of Civil and Environmental Engineering, Florida International Univ., Miami, FL.

4. Assistant Professor, Moss Dept. of Construction Management, Florida International Univ., Miami, FL.

Publisher

American Society of Civil Engineers

Reference23 articles.

1. Assessment and prediction of mechanical strength of jute fibre reinforced recycled aggregate concrete;Ahmed M.;IJSMSS,2021

2. Akkaya, B., and N. Çolakoğlu. 2019. “Comparison of multi-class classification algorithms on early diagnosis of heart diseases.” In Proc., y-BIS 2019 Recent Advances in Data Science and Business Analytics, 162–170. Istanbul, Turkey: International Society for Business and Industrial Statistics.

3. Developing Bridge Deterioration Models Using an Artificial Neural Network

4. Landslide susceptible areas identification using IDW and Ordinary Kriging interpolation techniques from hard soil depth at middle western Central Java, Indonesia

5. Deep learning-based detection of structural damage using time-series data

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