DEEP LEARNING APPROACH FOR DATA-DRIVEN SURROGATE MODELING IN STOCHASTIC AND HETEROGENEOUS MATERIAL
This undergraduate thesis is about the development of data-driven neural network based surrogate models for stochastic and heterogeneous material analysis cases where the stochasticity of the material is modeled by Gaussian random fields. The goal of the surrogate model is to accept the random field...
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| Format: | Final Project |
| Language: | Indonesia |
| Online Access: | https://digilib.itb.ac.id/gdl/view/62011 |
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| Institution: | Institut Teknologi Bandung |
| Language: | Indonesia |