Dynamical Modeling and Data Clustering with Applications to Tick Population Dynamics and Finance

Abstract

Mathematical models are valuable tools that assist to control the spread of infected ticks and analyze tick-host dynamics. In this work, a compartmental model is created to study the dynamics of lone star ticks and white-tailed deers, with a focus on migration effect of white-tailed deers. The second model focuses on the effect of grooming behaviour of the host on tick dynamics. Lastly, a data set is separated using K-means and Birch clustering techniques and the silhouette score has been evaluated.