An evolutionary computing approach for reducing bias in the dynamic modulus predictive models of hot mix asphalt

Author:

Eleyedath Abhary,Krishna Swamy Aravind

Publisher

Elsevier BV

Subject

General Materials Science,Building and Construction,Civil and Structural Engineering

Reference45 articles.

1. Bennert, T.A., 2009.Dynamic modulus of hot mix asphalt, No. FHWA-NJ-2009-011, Rutgers University, New Jersey, NJ.

2. Mechanistic-empirical pavement design guide (MEPDG): a bird’s-eye view;Li;J. Modern Transportation,2011

3. A new simplistic model for dynamic modulus predictions of asphalt paving mixtures;Al-Khateeb;J. Association of Asphalt Paving Technol.,2006

4. Tree-based ensemble methods: predicting asphalt mixture dynamic modulus for flexible pavement design;Worthey;KSCE J. Civ. Eng.,2021

5. Developing hybrid machine learning models to determine the dynamic modulus (E*) of asphalt mixtures using parameters in witczak 1–40d model: A comparative study;Xu;Materials,2022

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