Advancing Population Dynamics Analysis: Leveraging AI-Enhanced Mathematical Techniques

Document Type

Conference Proceeding

Source of Publication

ACMLC 2024 - 2024 6th Asia Conference on Machine Learning and Computing

Publication Date

3-5-2025

Abstract

In this study, we blend advanced mathematical methods with AI to investigate structured population dynamics. Focusing on the 3rd generation AI techniques, especially numerical simulation, we aim to gain deep insights into population models and their behaviors. By transforming partial differential equations into ordinary differential equations, we conduct practical explorations with illustrative examples to showcase our discoveries. We particularly emphasize exploring the model's link with size-structured population models, enhancing our understanding of population dynamics. Our methodology seamlessly integrates the tight frame representation method with collocation, enabling resolution of complex partial differential equations and facilitating more precise simulations through AI-driven analysis of numerical solutions.

ISBN

[9798400710018]

Publisher

ACM

First Page

146

Last Page

150

Disciplines

Computer Sciences | Mathematics

Keywords

artificial intelligence AI, Competition models, ordinary differential equations, partial differential equations, size-structured population dynamics, tight frames

Scopus ID

05001153089

Indexed in Scopus

yes

Open Access

no

Link to Full Text

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