Search Results for author:
Found 4 papers, 1 papers with code
Comparison of Single- and Multi- Objective Optimization Quality for Evolutionary Equation Discovery
Evolutionary differential equation discovery proved to be a tool to obtain equations with less a priori assumptions than conventional approaches, such as sparse symbolic regression over the complete possible terms library.
Model-agnostic multi-objective approach for the evolutionary discovery of mathematical models
In modern data science, it is often not enough to obtain only a data-driven model with a good prediction quality.
Multi-objective discovery of PDE systems using evolutionary approach
However, this approach restricts the application to the real cases, where, for example, the form of the external forcing is of interest.
The data-driven physical-based equations discovery using evolutionary approach
The selected terms pass to the evolutionary algorithm, which is used to evolve the selection.
Cannot find the paper you are looking for? You can
Submit a new open access paper.
