The UCF Mathematics Colloquium, held every Monday from 3:30pm to 4:30pm in MSB 318, offers a diverse platform for research scholars, faculty, students, and industry experts to share and exchange ideas, fostering discussion and networking across various areas of mathematics.
Dr. Xinyue Zhao, from University of Tennessee, Knoxville, will speak at this week's colloquium on neural-network-based methods for solving free boundary problems.
Abstract: Free boundary problems (the time-dependent versions are also often known as moving boundary problems) deal with systems of partial differential equations (PDEs) where the domain boundary is apriori unknown. Due to this special characteristic, it is challenging to solve free boundary problem numerically, and most studies in this field lack convergence proofs for the numerical methods. In this talk, I will present novel approaches based on neural networks to study two types of free boundary problems: 1) the classical obstacle problem, and 2) a modified Hele-Shaw problem. For each method we proposed, we established the convergence of the scheme and theoretically derived the convergence rate with the number of neurons. Several simulation examples are used to demonstrate the feasibility and capability of the proposed methods.
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