Pham BT - Search Results

1

Artificial Intelligence Approaches for Prediction of Compressive Strength of Geopolymer Concrete.

Dao DV, Ly HB, Trinh SH, Le TT, Pham BT. Dao DV, et al. Among authors: pham bt. Materials (Basel). 2019 Mar 25;12(6):983. doi: 10.3390/ma12060983. Materials (Basel). 2019. PMID: 30934566 Free PMC article.

2

Development of artificial intelligence models for the prediction of Compression Coefficient of soil: An application of Monte Carlo sensitivity analysis.

Pham BT, Nguyen MD, Dao DV, Prakash I, Ly HB, Le TT, Ho LS, Nguyen KT, Ngo TQ, Hoang V, Son LH, Ngo HTT, Tran HT, Do NM, Van Le H, Ho HL, Tien Bui D. Pham BT, et al. Sci Total Environ. 2019 Aug 20;679:172-184. doi: 10.1016/j.scitotenv.2019.05.061. Epub 2019 May 7. Sci Total Environ. 2019. PMID: 31082591

3

Prediction and Sensitivity Analysis of Bubble Dissolution Time in 3D Selective Laser Sintering Using Ensemble Decision Trees.

Ly HB, Monteiro E, Le TT, Le VM, Dal M, Regnier G, Pham BT. Ly HB, et al. Among authors: pham bt. Materials (Basel). 2019 May 10;12(9):1544. doi: 10.3390/ma12091544. Materials (Basel). 2019. PMID: 31083456 Free PMC article.

4

Hybrid Artificial Intelligence Approaches for Predicting Buckling Damage of Steel Columns Under Axial Compression.

Le LM, Ly HB, Pham BT, Le VM, Pham TA, Nguyen DH, Tran XT, Le TT. Le LM, et al. Among authors: pham ta, pham bt. Materials (Basel). 2019 May 22;12(10):1670. doi: 10.3390/ma12101670. Materials (Basel). 2019. PMID: 31121948 Free PMC article.

5

Development of an AI Model to Measure Traffic Air Pollution from Multisensor and Weather Data.

Ly HB, Le LM, Phi LV, Phan VH, Tran VQ, Pham BT, Le TT, Derrible S. Ly HB, et al. Among authors: pham bt. Sensors (Basel). 2019 Nov 13;19(22):4941. doi: 10.3390/s19224941. Sensors (Basel). 2019. PMID: 31766187 Free PMC article.

6

Flocculation-dewatering prediction of fine mineral tailings using a hybrid machine learning approach.

Qi C, Ly HB, Chen Q, Le TT, Le VM, Pham BT. Qi C, et al. Among authors: pham bt. Chemosphere. 2020 Apr;244:125450. doi: 10.1016/j.chemosphere.2019.125450. Epub 2019 Nov 25. Chemosphere. 2020. PMID: 31816548

7

Investigation and Optimization of the C-ANN Structure in Predicting the Compressive Strength of Foamed Concrete.

Dao DV, Ly HB, Vu HT, Le TT, Pham BT. Dao DV, et al. Among authors: pham bt. Materials (Basel). 2020 Feb 28;13(5):1072. doi: 10.3390/ma13051072. Materials (Basel). 2020. PMID: 32121104 Free PMC article.

8

Optimization of Artificial Intelligence System by Evolutionary Algorithm for Prediction of Axial Capacity of Rectangular Concrete Filled Steel Tubes under Compression.

Nguyen HQ, Ly HB, Tran VQ, Nguyen TA, Le TT, Pham BT. Nguyen HQ, et al. Among authors: pham bt. Materials (Basel). 2020 Mar 7;13(5):1205. doi: 10.3390/ma13051205. Materials (Basel). 2020. PMID: 32156033 Free PMC article.

9

Parametric Investigation of Particle Swarm Optimization to Improve the Performance of the Adaptive Neuro-Fuzzy Inference System in Determining the Buckling Capacity of Circular Opening Steel Beams.

Nguyen QH, Ly HB, Le TT, Nguyen TA, Phan VH, Tran VQ, Pham BT. Nguyen QH, et al. Among authors: pham bt. Materials (Basel). 2020 May 12;13(10):2210. doi: 10.3390/ma13102210. Materials (Basel). 2020. PMID: 32408473 Free PMC article.

10

Cost-Effective Approaches Based on Machine Learning to Predict Dynamic Modulus of Warm Mix Asphalt with High Reclaimed Asphalt Pavement.

Dao DV, Nguyen NL, Ly HB, Pham BT, Le TT. Dao DV, et al. Among authors: pham bt. Materials (Basel). 2020 Jul 23;13(15):3272. doi: 10.3390/ma13153272. Materials (Basel). 2020. PMID: 32717910 Free PMC article.

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