I want to make a model to simulate the state performance of a certain grid point in a cell body in different states. I use a neural network model to build it. I don't know how to divide the finite elements reasonably. That is, with a grid point as the center, the problem of selecting its adjacent points.
It seems you're dealing with two key aspects here, finite element analysis (FEA) and neural network-based state prediction.
To integrate the two, you could potentially use the results of the FEA as input to your neural network model. For example, you could perform FEA under different conditions, and use the resulting state of each grid point and its neighbors as training data for the neural network.
Lastly, remember that both FEA and neural networks are complex tools that require a deep understanding of the underlying principles and techniques to use effectively. Always check your results for reasonableness and consistency, and be prepared to adjust your models and methods based on your results as needed.
- Badges
- Science topic
- Similar topics
- Biological Science
- Molecular Cell Biology
- Culture Cells
- Cell Line