Fish migration models using self-exciting stochastic processes

Project level: Honours, PhD

This project aims to study the population dynamics of migratory fish species, which are known to be highly random and complex because of the flocking and social interactions in fish migration. The objective is to develop a stochastic process model using self-exciting processes, such as branching and Hawkes, some of which can be constructed by applying Brownian motion and Poisson processes. Additionally, we are interested in numerical methods using Monte Carlo simulation and finite difference methods.