Model Discovery for Nonlinear Ordinary Differential Equations and Partial Differential Equations

For the first part, I used linear fitting to a library of functions to derive a system of two first order differential equations that characterize snowshoe hare and lynx population data over a period of 30 years. I compared various models of linear fittings using Kullback–Leibler (KL) Divergence, the Akaike Information Criterion (AIC), and the Bayesian Information Criterion (BIC). For the second part, I used linear fitting to a library of functions to derive a partial differential equation that characterizes video of a Belousov-Zhabotinsky Chemical oscillator. I compared various models using KL Divergence.

The full paper describing this project is here.

Hare and Lynx Phase Diagram, Data, Red; Quintic Fit, Blue.
Lynx Population – Data, Red; Quintic Fit, Blue.
Lynx Population – Data, Red; Lotka-Volterra Equation Fit, Blue.

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