Mokhtar Mohammadi 
- (2022): Developing six hybrid machine learning models based on gaussian process regression and meta-heuristic optimization algorithms for prediction of duration and cost of road tunnels construction. In: Tunnelling and Underground Space Technology, v. 130 (Dezember 2022).
- (2022): Extreme learning machine evolved by fuzzified hunger games search for energy and individual thermal comfort optimization. In: Journal of Building Engineering, v. 60 (November 2022).
- (2022): Optimized machine learning modelling for predicting the construction cost and duration of tunnelling projects. In: Automation in Construction, v. 139 (Juli 2022).
- (2021): Predicting construction time and cost of tunnels using Markov chain model considering opinions of experts. In: Tunnelling and Underground Space Technology, v. 116 (Oktober 2021).
- (2021): Machine learning forecasting models of disc cutters life of tunnel boring machine. In: Automation in Construction, v. 128 (August 2021).
- (2021): Presenting the best prediction model of water inflow into drill and blast tunnels among several machine learning techniques. In: Automation in Construction, v. 127 (Juli 2021).
- (2021): Dynamic reduction of time and cost uncertainties in tunneling projects. In: Tunnelling and Underground Space Technology, v. 109 (März 2021).
- (2021): Forecasting sidewall displacement of underground caverns using machine learning techniques. In: Automation in Construction, v. 123 (März 2021).
- (2020): Forecasting maximum surface settlement caused by urban tunneling. In: Automation in Construction, v. 120 (Dezember 2020).
- (2020): Decision-making in tunneling using artificial intelligence tools. In: Tunnelling and Underground Space Technology, v. 103 (September 2020).
- (2019): Updating ground conditions and time-cost scatter-gram in tunnels during excavation. In: Automation in Construction, v. 105 (September 2019).
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