Mohamed El Amine Ben Seghier 
- (2024): A new formulation for predicting the ultimate capacities of FRP-confined concrete using advanced machine learning framework: Developed structural reliability analysis. Dans: Structures, v. 68 (octobre 2024).
- (2024): Two-stage framework for lateral-torsional buckling resistance prediction of cellular steel beams under fire conditions. Dans: Structures, v. 68 (octobre 2024).
- (2024): Machine learning-based Shapley additive explanations approach for corroded pipeline failure mode identification. Dans: Structures, v. 65 (juillet 2024).
- (2023): Application of machine learning approaches for modelling crack growth rates. Dans: ce/papers, v. 6, n. 3-4 (septembre 2023).
- (2023): Assessment of artificial intelligence‐ based techniques for the estimation of pile group scour depth. Dans: ce/papers, v. 6, n. 5 (septembre 2023).
- (2023): Predicting Wall Thickness Loss in Water Pipes Using Machine Learning Techniques. Dans: ce/papers, v. 6, n. 5 (septembre 2023).
- (2023): Scrutinizing the Performances of Hybrid ANN Models for Forecasting Condition of Bridges. Dans: ce/papers, v. 6, n. 5 (septembre 2023).
- (2023): A Novel Chaotic Optimization‐Oriented Model for Bridge Maintenance and Rehabilitation Planning. Dans: ce/papers, v. 6, n. 5 (septembre 2023).
- (2023): Metaheuristic‐based machine learning modeling of the compressive strength of concrete containing waste glass. Dans: Structural Concrete, v. 24, n. 4 (5 juillet 2023).
- (2022): Integrity of API 5L X56 Offshore Pipeline Subjected to Girth Weld Anomalies and Corrosion Using Probabilistic Methods. Dans: Journal of Performance of Constructed Facilities (ASCE), v. 36, n. 5 (octobre 2022).
- (2022): Random forest-based algorithms for accurate evaluation of ultimate bending capacity of steel tubes. Dans: Structures, v. 44 (octobre 2022).
- (2019): Sensitivity of reliability-based fatigue analysis to crack shape development in cracked pipeline. Dans: Procedia Structural Integrity, v. 22 ( 2019).
- (2021): Accurate Structural Reliability Analysis Using an Improved Line-Sampling-Method-Based Slime Mold Algorithm. Dans: ASCE-ASME Journal of Risk and Uncertainty in Engineering Systems, Part A: Civil Engineering, v. 7, n. 2 (juin 2021).
- (2021): Modeling the nonlinear behavior of ACC for SCFST columns using experimental-data and a novel evolutionary-algorithm. Dans: Structures, v. 30 (avril 2021).
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