MS006B Uncertainty quantification and design optimization of complex structures and innovative construction process using machine learning II
Main Organizer:
Dr.
Duc Phi Do
(
University of Orleans
, France
)
Chaired by:
Dr. Duc Phi Do (University of Orleans , France) , Prof. Dashnor HOXHA (Laboratory of MEchanics, Gabriel Lamé, University of Orleans , France)
Dr. Duc Phi Do (University of Orleans , France) , Prof. Dashnor HOXHA (Laboratory of MEchanics, Gabriel Lamé, University of Orleans , France)
Scheduled presentations:
-
Grammar-Based Generative Design of Truss Structures with Monte Carlo Tree Search
-
Student
Incorporating Uncertainties of EBFs using various Machine Learning Methods and Sampling-based Reliability Approaches
-
Student
Time-dependent convergence prediction, uncertainty quantification of creep rock behavior and design optimization of deep tunnel support using ai methods
-
Optimlized LSTM Neural Networks via Neural Architecture Search for Predicting Damage Evolution in Composite Laminates
-
Student
A Two-Stage Metamodeling Approach for Efficient Global Robust Optimization
-
Student
Efficient Robust Optimization of Network Systems under Uncertainty
