Machine learning for predicting concrete carbonation depth: A comparative analysis and a novel feature selection

M Ehsani, M Ostovari, S Mansouri, H Naseri… - … and Building Materials, 2024 - Elsevier
The accurate prediction of concrete carbonation depth is essential to prevent concrete from
cracking and corrosion. However, identifying the critical parameters affecting carbonation …

Surface concrete cracks detection and segmentation using transfer learning and multi-resolution image processing

M Iraniparast, S Ranjbar, M Rahai, FM Nejad - Structures, 2023 - Elsevier
Surface crack detection must be precise and efficient for the structural health monitoring
(SHM) of concrete structures. The traditional techniques of crack detection entail human …

[HTML][HTML] Assessment of the level of road crash severity: comparison of intelligence studies

SS Haghshenas, G Guido, A Vitale, V Astarita - Expert systems with …, 2023 - Elsevier
In measuring road safety, accident severity is a key concern. Crash severity prediction
models inform researchers about the severity of a crash based on a variety of criteria. To …

Machine learning approaches for estimating interfacial tension between oil/gas and oil/water systems: a performance analysis

F Yousefmarzi, A Haratian, J Mahdavi Kalatehno… - Scientific Reports, 2024 - nature.com
Interfacial tension (IFT) is a key physical property that affects various processes in the oil and
gas industry, such as enhanced oil recovery, multiphase flow, and emulsion stability …

Optimized prediction models for faulting failure of Jointed Plain concrete pavement using the metaheuristic optimization algorithms

M Ehsani, P Hamidian, P Hajikarimi… - Construction and Building …, 2023 - Elsevier
This study aims to predict faulting failure of jointed plain concrete pavement (JPCP) using
different variables. For this purpose, four feature selection methods were developed by …

[HTML][HTML] Enhancing road safety with machine learning: Current advances and future directions in accident prediction using non-visual data

ABZ Chai, BT Lau, MKT Tee, C McCarthy - Engineering Applications of …, 2024 - Elsevier
Road traffic accident (RTA) poses a significant road safety issue due to the increased
fatalities worldwide. To address it, various artificial intelligence solutions are developed to …

Developing deterministic and probabilistic prediction models to evaluate high-temperature performance of modified bitumens

M Ehsani, P Hajikarimi, M Esfandiar, M Rahi… - … and Building Materials, 2023 - Elsevier
This study aims to develop deterministic and probabilistic prediction models for the multiple
stress creep and recovery (MSCR) test. For this purpose, crumb rubber, polyphosphoric …

Data-Driven Approaches for Accident Analysis in Sociochemical Systems

K Gholamizadeh, E Zarei, M Yazdi, MT Amin - Safety Causation Analysis in …, 2024 - Springer
Accident analysis is crucial for gaining a deep understanding of system malfunctions and
preventing catastrophic events, along with potential human, financial, and environmental …

[HTML][HTML] Sustainable crumb rubber modified asphalt mixtures based on low-temperature crack propagation characteristics using the response surface methodology

S Ghafari, S Ranjbar, M Ehsani, FM Nejad… - Theoretical and Applied …, 2023 - Elsevier
Fracture regime of asphalt concrete is of utmost importance in the sustainable design of
optimized mixtures against low-temperature cracking. The energy dissipated in blunting the …

Optimal waste load allocation in river systems based on a new multi-objective cuckoo optimization algorithm

S Haghdoost, MH Niksokhan, MG Zamani… - … Science and Pollution …, 2023 - Springer
Water pollution escalates with rising waste discharge in river systems, as the rivers' limited
pollution tolerance and constrained self-cleaning capacity compel the release of treated …