Nonlinear Genetic-Based Models for Prediction of Flow Number of Asphalt Mixtures

By Amir H. Gandomi, Amir Hossein Alavi, Mohammadreza Mirzahosseini, Fereidoon Moghadas Nejad. 2011

285 citations recorded by the source corpus.

Subfields: Civil and Structural Engineering

View Paper: https://www.semanticscholar.org/paper/002cdf06d21322cfcbb4b3f90aa7fd33bd9ff591

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Civil and Structural Engineering

1. Muhammad Faisal Javed
2. Shazim Ali memon
3. Muhammad Khizar Khan
4. Rayed Alyousef
5. Iyad Alkroosh
6. Furqan Farooq
7. Hamid Nikraz
8. Fahid Aslam

Citations in the corpus

• Compressive Strength of Fly-Ash-Based Geopolymer Concrete by Gene Expression Programming and Random Forest (2021, methodology): “Some limitation of regression analysis like the use of predefined equations either nonlinear or linear and preassumption of residuals normality restricts its application [111], while GEP modelling chooses the nonlinear relation between input and output parameters effectively and provides a higher ge”
• Predicting pile dynamic capacity via application of an evolutionary algorithm (2014, methodology): “Recently, GEP has been applied successfully in solving engineering problems (e.g. Cevic and Cabalar, 2009; Alkroosh and Nikraz, 2011a, 2011b; Gandomi, 2011; Gandomi and Alavi, 2012).”