A Semi-Automatic Numerical Algorithm for Turing Patterns Formation in a Reaction-Diffusion Model

Abstract

The Turing pattern formation is modeled by reaction-diffusion (RD) type partial differential equations, and it plays a crucial role in ecological studies. Big data analytics and suitable frameworks to manage and predict structures and configurations are mandatory. The processing and resolution procedures of mathematical models relies upon numerical schemes, and concurrently upon the related automated algorithms. Starting from a RD model for vegetation patterns, we propose a semi-automatic algorithm based on a smart numerical criterion for observing ecological reliable results. Numerical experiments are carried out in the case of spot's formations.

Keywords

• Vegetation turing patterns
• finite difference methods
• Internet of Things