About this document
Data-Driven Discovery of Partial Differential Equations by Marce is a document available to read on EtoBox.
The document presents a sparse regression method for discovering governing partial differential equations (PDEs) from time series data in spatial domains. This method utilizes sparsity-promoting techniques to efficiently identify relevant terms in the equations, balancing model complexity and accuracy through Pareto analysis. It demonstrates effectiveness on various canonical problems in mathematical physics, such as the Navier-Stokes equations and the diffusion equation, and provides a new approach for unc
- Author
- Marce
- Language
- EN