The data analysis task of determining a model for an ordinary differential equation (ODE) system from given noisy solution data is addressed. Since modeling with ODE is ubiquitous in science and technology, finding ODE models from data is of paramount importance. Based on a previously published parameter estimation method for ODE models, four related model estimation algorithms were developed. The algorithms are tested for over 20 different polynomial ordinary equation systems comprising 60 equations at various noise levels. Two algorithms frequently compute the correct model. They are compared to the prominent SINDy-family for those SINDy-algorithms that have simple default hyperparameters. This demonstrates that they are comparable to SINDy and more resilient towards noise than the tested SINDy algorithms.
The data analysis task of determining a model for an ordinary differential equation system (ODE) from given noisy solution data is addressed. Based on a previously published parameter estimation method for ODE models four related model estimation algorithms were developed. The algorithms are tested for over 20 different polynomial ordinary equation systems comprising 60 equations at various noise levels. Two algorithms frequently compute the correct model.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.