Pages that link to "Item:Q6158472"
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The following pages link to An artificial neural network approach to bifurcating phenomena in computational fluid dynamics (Q6158472):
Displaying 13 items.
- Neural network modeling for near wall turbulent flow. (Q1868544) (← links)
- Numerical simulation and predictive modeling of an inextensible filament in two-dimensional viscous shear flow using the immersed boundary/coarse-graining method and artificial neural networks (Q2096822) (← links)
- A comparison of reduced-order modeling approaches using artificial neural networks for PDEs with bifurcating solutions (Q2672190) (← links)
- Neural networks for BEM analysis of steady viscous flows (Q4422586) (← links)
- Neural network-based modelling of subsonic cavity flows (Q5402730) (← links)
- Artificial Neural Network (ANN) Model for Prediction of Mixing Behavior of Granular Flows (Q5451495) (← links)
- Artificial neural network based correction for reduced order models in computational fluid mechanics (Q6096479) (← links)
- A graph convolutional autoencoder approach to model order reduction for parametrized PDEs (Q6126547) (← links)
- Inferring bifurcation diagrams with transformers (Q6555010) (← links)
- Mathematical modelling and computational reduction of molten glass fluid flow in a furnace melting basin (Q6616176) (← links)
- Artificial neural network design for non linear Takagi-Sugeno systems: application to tracking of trajectory, state and fault estimation of MIABOT robot (Q6618992) (← links)
- On the latent dimension of deep autoencoders for reduced order modeling of PDEs parametrized by random fields (Q6624464) (← links)
- GFN: a graph feedforward network for resolution-invariant reduced operator learning in multifidelity applications (Q6643617) (← links)
