Minh-Tu Cao 
- (2023): Drone-assisted segmentation of tile peeling on building façades using a deep learning model. Dans: Journal of Building Engineering, v. 80 (décembre 2023).
- (2023): Advanced soft computing techniques for predicting punching shear strength. Dans: Journal of Building Engineering, v. 79 (novembre 2023).
- (2023): Accurately predicting the mechanical behavior of deteriorated reinforced concrete components using natural intelligence-integrated Machine learners. Dans: Construction and Building Materials, v. 408 (décembre 2023).
- (2023): Early estimation of the long-term deflection of reinforced concrete beams using surrogate models. Dans: Construction and Building Materials, v. 370 (mars 2023).
- (2022): Smart ensemble machine learner with hyperparameter-free for predicting bond capacity of FRP-to-concrete interface: Multi-national data. Dans: Construction and Building Materials, v. 345 (août 2022).
- (2022): Using an evolutionary heterogeneous ensemble of artificial neural network and multivariate adaptive regression splines to predict bearing capacity in axial piles. Dans: Engineering Structures, v. 268 (octobre 2022).
- (2022): Hybrid artificial intelligence-based inference models for accurately predicting dam body displacements: A case study of the Fei Tsui dam. Dans: Structural Health Monitoring, v. 21, n. 4 (janvier 2022).
- (2021): Dynamic Feature Selection for Accurately Predicting Construction Productivity Using Symbiotic Organisms Search-Optimized Least Square Support Vector Machine. Dans: Journal of Building Engineering, v. 35 (mars 2021).
- (2016): Estimating Strength of Rubberized Concrete Using Evolutionary Multivariate Adaptive Regression Splines. Dans: Journal of Civil Engineering and Management, v. 22, n. 5 (mai 2016).
- (2016): Chaotic Initialized Multiple Objective Differential Evolution With Adaptive Mutation Strategy (ca-mode) for Construction Project Time-cost-quality Trade-off. Dans: Journal of Civil Engineering and Management, v. 22, n. 2 (mars 2016).
- (2016): Solving Resource-Constrained Project Scheduling Problems Using Hybrid Artificial Bee Colony with Differential Evolution. Dans: Journal of Computing in Civil Engineering, v. 30, n. 4 (juillet 2016).
- (2015): Predicting Equilibrium Scour Depth at Bridge Piers Using Evolutionary Radial Basis Function Neural Network. Dans: Journal of Computing in Civil Engineering, v. 29, n. 5 (septembre 2015).
- (2015): Hybrid Computational Model for Forecasting Taiwan Construction Cost Index. Dans: Journal of Construction Engineering and Management, v. 141, n. 4 (avril 2015).
- (2014): A hybrid fuzzy inference model based on RBFNN and artificial bee colony for predicting the uplift capacity of suction caissons. Dans: Automation in Construction, v. 41 (mai 2014).
- (2015): Hybrid intelligent inference model for enhancing prediction accuracy of scour depth around bridge piers. Dans: Structure and Infrastructure Engineering, v. 11, n. 9 (septembre 2015).
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