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