A machine learning study of the dynamic modulus of asphalt concretes: An application of M5P model tree algorithm

Deep Convolutional Neural Networks with transfer learning for computer vision-based data-driven pavement distress detection

Kasthurirangan Gopalakrishnan, Siddhartha Kumar Khaitan, Alok Choudhary et al. · Construction and Building Materials · 2017 · 947 citations · Full text

Computing, Civil Engineering, Computer Science +14

Induction of model trees for predicting continuous classes

Yong Wang, Ian H. Witten · Research Commons (The University of Waikato) · 1996 · 689 citations · Full text

Computing, Computer Science, Mathematics +12

Morphology, rheology, and physical properties of polymer-modified asphalt binders

Ali Behnood, Mahsa Modiri Gharehveran · European Polymer Journal · 2018 · 594 citations

Engineering, Materials Engineering, Materials Science +14

Predicting the compressive strength of normal and High-Performance Concretes using ANN and ANFIS hybridized with Grey Wolf Optimizer

Emadaldin Mohammadi Golafshani, Ali Behnood, Mehrdad Arashpour · Construction and Building Materials · 2019 · 467 citations

Engineering, Civil Engineering, Materials Engineering +16

Predicting the compressive strength of silica fume concrete using hybrid artificial neural network with multi-objective grey wolves

Ali Behnood, Emadaldin Mohammadi Golafshani · Journal of Cleaner Production · 2018 · 342 citations

Engineering, Civil Engineering, Materials Engineering +14