Ali Shariati

A novel hybrid extreme learning machine–grey wolf optimizer (ELM-GWO) model to predict compressive strength of concrete with partial replacements for cement

Mahdi Shariati, Mohammad Saeed Mafipour, Behzad Ghahremani et al. · Engineering With Computers · 2020 · 341 citations

Engineering, Machine Learning, Extreme Learning Machine +8

Effect of pumice powder and nano-clay on the strength and permeability of fiber-reinforced pervious concrete incorporating recycled concrete aggregate

Peyman Mehrabi, Mahdi Shariati, Kamyar Kabirifar et al. · Construction and Building Materials · 2021 · 216 citations

Engineering, Environmental Engineering, Fiber-reinforced Pervious Concrete +8

Application of support vector machine with firefly algorithm for investigation of the factors affecting the shear strength of angle shear connectors

E. Sadeghipour Chahnasir, Yousef Zandi, Mahdi Shariati et al. · Zenodo (CERN European Organization for Nuclear Research) · 2018 · 173 citations · Full text

A novel approach to predict shear strength of tilted angle connectors using artificial intelligence techniques

Mahdi Shariati, Mohammad Saeed Mafipour, Peyman Mehrabi et al. · Engineering With Computers · 2020 · 170 citations

Structural Integrity, Engineering, Artificial Intelligence Techniques +12

Comparative performance of channel and angle shear connectors in high strength concrete composites: An experimental study

Mahdi Shariati, N.H. Ramli Sulong, Ali Shariati et al. · Construction and Building Materials · 2016 · 150 citations

Fiber Reinforcement, Engineering, Civil Engineering +8