Lý Hải Bằng
Tiến sĩ
Trường Đại học Công nghệ Giao thông vận tải
Đơn vị: Khoa Công trình
Quá trình nghiên cứu khoa học
- stars 1. Các đề tài nghiên cứu khoa học đã tham gia
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TTTên đề tàiNăm hoàn thànhĐề tài cấp
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Chưa có thông tin
- stars 2. Các công trình khoa học đã công bố
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TTTên công trìnhNămNơi công bố
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1Flocculation-dewatering prediction of fine mineral tailings using a hybrid machine learning approach2020Chemosphere, Volume 244, April 2020, pp 1-16
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2Landslide susceptibility modeling using different artificial intelligence methods: a case study at Muong Lay district, Vietnam2019Geocarto International, 1-24 https://doi.org/10.1080/10106049.2019.1665715
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3Quantification of Uncertainties on the Critical Buckling Load of Columns under Axial Compression with Uncertain Random Materials2019Materials, Volume 12 Issue 11, pp1-19
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4Macroscopic permeability of doubly porous materials with cylindrical and spherical macropores2019Meccanica, 02 August 2019, pp 1–14,
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5Analysis of Tourist Travel Behavior and Recommendation for Active Transport Encouragement Strategies, the Case of Hue City2019CIGOS 2019, Innovation for Sustainable Infrastructure, Lecture Notes in Civil Engineering 54, pp 1049-1055
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6A Possibility of AI Application on Mode-choice Prediction of Transport Users in Hanoi2019CIGOS 2019, Innovation for Sustainable Infrastructure, Lecture Notes in Civil Engineering 54, pp 1179-1184
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7Development of Artificial Neural Networks for Prediction of Compression Coefficient of Soft Soil2019CIGOS 2019, Innovation for Sustainable Infrastructure, Lecture Notes in Civil Engineering 54, pp 1167-1172
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8Adaptive Network Based Fuzzy Inference System with Meta-Heuristic Optimizations for International Roughness Index Prediction2019Applied Sciences (Switzerland), Volume 9 Issue 21, 5 November 2019, pp 1-18
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9Development of an AI Model to Measure Traffic Air Pollution from Multisensor and Weather Data2019Sensors, Volume 19, Issue 22, pp 1-17, 13 November 2019
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10Improvement of ANFIS Model for Prediction of Compressive Strength of Manufactured Sand Concrete2019Applied Sciences (Switzerland), Volume 9 Issue 18, 12 September 2019, pp 1-16
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11Development of Hybrid Machine Learning Models for Predicting the Critical Buckling Load of I-Shaped Cellular Beams2019Applied Sciences (Switzerland), Volume 9 Issue 24, 12 December 2019, pp 1-21,
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12A Novel Intelligence Approach of a Sequential Minimal Optimization-Based Support Vector Machine for Landslide Susceptibility Mapping2019Sustainability, Volume 11, Issue 22, pp 1-31
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13Development of 48-hour Precipitation Forecasting Model using Nonlinear Autoregressive Neural Network2019CIGOS 2019, Innovation for Sustainable Infrastructure, Lecture Notes in Civil Engineering 54, pp 1191-1196
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14Development of Hybrid Artificial Intelligence Approaches and a Support Vector Machine Algorithm for Predicting the Marshall Parameters of Stone Matrix Asphalt2019Applied Sciences 9 (15), 3172
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15Temperature effects on chloride binding capacity of cementitious materials2019Magazine of Concrete Research, 1-39
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16Artificial Intelligence Approaches for Prediction of Compressive Strength of Geopolymer Concrete2019Materials 12 (6), 983
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17Prediction of Compressive Strength of Geopolymer Concrete Using Entirely Steel Slag Aggregates: Novel Hybrid Artificial Intelligence Approaches2019Applied Sciences 9 (6), 1113
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18Prediction and Sensitivity Analysis of Bubble Dissolution Time in 3D Selective Laser Sintering Using Ensemble Decision Trees2019Materials 12 (9), 1544
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19Hybrid Artificial Intelligence Approaches for Predicting Buckling Damage of Steel Columns Under Axial Compression2019Materials 12 (10), 1670
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20Development of artificial intelligence models for the prediction of Compression Coefficient of soil: An application of Monte Carlo sensitivity analysis2019Science of The Total Environment 679, 172-184
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21Hybrid Artificial Intelligence Approaches for Predicting Critical Buckling Load of Structural Members under Compression Considering the Influence of Initial Geometric Imperfections2019Appl. Sci. 2019, 9, 2258
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22A comparative assessment of flood susceptibility modeling using Multi- Criteria Decision-Making Analysis and Machine Learning Methods2019Journal of Hydrology 573 (2019) 311–323
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23On the factors affecting porosity dissolution in selective laser sintering process2018AIP Conference Proceedings 1960 (1), 120014
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24Versatile functionalization platform of biporous poly (2-hydroxyethyl methacrylate)-based materials: Application in heterogeneous supported catalysis2017Reactive and Functional Polymers 121, 91-100
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25Biporous polymeric materials with controlled pore size and connectivity2016ABSTRACTS OF PAPERS OF THE AMERICAN CHEMICAL SOCIETY 252
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26Biporous Crosslinked Polymers With Controlled Pore Size and Connectivity2016Macromolecular Symposia 365 (1), 49-58
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27Functionalized Doubly Porous Networks: From Synthesis to Application in Heterogeneous Catalysis2016Macromolecular Symposia 365 (1), 40-48
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28Computation of permeability with Fast Fourier Transform from 3-D digital images of porous microstructures2016International Journal of Numerical Methods for Heat & Fluid Flow 26 (5)
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29Tailoring doubly porous poly (2-hydroxyethyl methacrylate)-based materials via thermally induced phase separation2016Polymer 86, 138-146
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30Facile fabrication of doubly porous polymeric materials with controlled nano-and macro-porosity2015Polymer 78, 13-21
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31Designing and modeling doubly porous polymeric materials2015The European Physical Journal Special Topics 224 (9), 1689-1706
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32Functional doubly porous materials based on polymer networks2014ABSTRACTS OF PAPERS OF THE AMERICAN CHEMICAL SOCIETY 248
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33Novel Polymeric Materials with Double Porosity: Synthesis and Characterization2014Macromolecular Symposia 340 (1), 18-27
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34Engineering functional doubly porous PHEMA-based materials2014Polymer 55 (1), 373-379
- stars 3. Giáo trình, tài liệu đã xuất bản
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TTTên giáo trình, tài liệuNămNơi xuất bản
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Chưa có thông tin
- stars 4. Hướng dẫn sau đại học
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TTHọc viênTên luận văn, luận ánNăm hoàn thành
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Chưa có thông tin