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| 1 | Neural Networks in Engineering Applications | |
| 1.1 | Digital Twin of the Reinforced Concrete Slab Based on the Artificial Neural Network P. Lacki, A. Derlatka, J. Niemiro-Maźniak and M. Lacki |
10 |
| 1.2 | Conceptualizing an AI-based Effective Stiffness Analysis of Human Trabecular Bone J. Gebert, F. Pelzer and M.M. Resch |
13 |
| 1.3 | Deep Learning Methods for the Analysis of Townscapes S. Balestra, O. Hänni, M.-A. Iten, M. Blöchlinger, S. Bühler-Krebs and R.-P. Mundani |
10 |
| 1.4 | Enhancing Information Flow in Graph Neural Networks for Scientific Machine Learning M. Chenaud, J. Alves and F. Magoulès |
14 |
| 1.5 | A Physics-Informed Neural Network Approach to Estimating the Coefficient of Consolidation in Geotechnical Engineering S. Pramanik and J. Inoue |
8 |
| 2 | Neural Networks-Based Deep Learning for Next-Generation Engineering Optimization, organized by: Prof. Majid Movahedi Rad, Dr. Raffaele Cucuzza, Dr. Marco Domaneschi, Dr. Muayad Habashneh, Dr. Hamed Fathnejat | |
| 2.1 | Construction Planning Based on Lagrange Optimization With Artificial Neural Network W.-K. Hong and T.D. Pham |
12 |
| 2.2 | MLP Neural Networks To Identify Damage in Bridges From SHM Data A. Montisci, F. Pibi and M.C. Porcu |
14 |
| 2.3 | Improved TLBO Algorithm for Truss Size Optimization Considering Geometric Nonlinearity M. Habashneh and M. Movahedi Rad |
10 |
| 2.4 | Geometrically Nonlinear Shape Optimization of Elasto-Plastic Trusses Using a Neural Network-Assisted Genetic Algorithm P. Grubits and M. Movahedi Rad |
13 |
| 3 | Innovative Methods for Structural Design and Optimization of Structures and Infrastructures, organized by: Dr. Raffaele Cucuzza, Prof. Majid Movahedi Rad, Dr. Marco Domaneschi, Prof. Giuseppe Carlo Marano | |
| 3.1 | Develop a Street Speed Bump Extraction and Mapping Framework From Street Level Imagery Using Deep Learning M. Abdel Karim, A. Alazmi and T. Alhadidi |
8 |
| 3.2 | Reinforcement Learning-Based Control Strategy for Semi-Active Energy Transfer in Beam Structures D. Bogucki, M. Ostrowski and B. Blachowski |
14 |
| 3.3 | Performance-Based Optimization of Steel Exoskeletons: An Alternative Approach to Standard Regulations J. Olivo, R. Cucuzza and G.C. Marano |
10 |
| 4 | New Trends in Applications of Machine Learning for Structural Optimization, organized by: Prof. Weisheng Zhang, Prof. Dong Li, Prof. Jian Zhang | |
| 4.1 | Crack-Safe Design Through PeriDynamic-Based SIMP Approach W. Zhang and Y. Liu |
10 |
| 4.2 | Machine Learning-Powered Geometry-Aware Filter: A Novel Human-Informed Approach for Advanced Topology Optimization X. Zhuang, W. Zhang, X. Guo and S.-K. Youn |
22 |
| 5 | AI-Based Topology Optimization and Metamaterials in Structural Design, organized by: Dr. Ismael Ben-Yelun, Lucía López-De-Abajo, Dr. Alberto Badías, Miguel Ángel Sanz-Gómez, José María Benítez, Prof. Francisco J. Montans | |
| 5.1 | HiCon-FEM: A Hierarchical Condensation Framework for Accelerated Topology Optimization V. Yanes, N.-H. Kim and F.J. Montans |
11 |
| 5.2 | Forward and Inverse Topology Optimization via Deep Rank-Reduction Autoencoders I. Ben-Yelun, M. El-Fallaki Idrissi, J. Mounayer, S. Rodríguez, F.J. Montans and F. Chinesta |
9 |