An unsupervised machine learning approach to reduce nonlinear FE2 multiscale calculations using macro clustering
Solving nonlinear multiscale methods with history-dependent behaviors and fine
macroscopic meshes is a well-known challenge. In this work, an unsupervised machine
learning-based clustering approach is developed to reduce nonlinear Multilevel Finite
Element-FE 2 calculations. In contrast with most available techniques which aim at
developing Reduced Order Models (ROM) or AI-based surrogate models for the microscale
nonlinear problems, the present technique reduces the problem from the macro scale by …
macroscopic meshes is a well-known challenge. In this work, an unsupervised machine
learning-based clustering approach is developed to reduce nonlinear Multilevel Finite
Element-FE 2 calculations. In contrast with most available techniques which aim at
developing Reduced Order Models (ROM) or AI-based surrogate models for the microscale
nonlinear problems, the present technique reduces the problem from the macro scale by …
[引用][C] An Unsupervised Machine Learning Approach to Reduce Nonlinear Multiscale Calculations Using Clustering
An Unsupervised Machine Learning Approach to Reduce Nonlinear Multiscale Calculations
Using Clustering - Université Gustave Eiffel …
Using Clustering - Université Gustave Eiffel …
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