Impact of population on forest loss in Mau Forest, Kenya using Machine Learning and Mathematical Modelling Approach
# Impact of Population Growth on Forest Loss in Mau Forest using Machine Learning and Mathematical Modelling Approach
## Overview
* This project explores how population growth affects forest loss in the Mau Forest, Kenya.
* Using a simulated dataset, the study applies multiple linear regression, differential equations, and data visualization in R to analyze relationships between population dynamics and environmental degradation.
### Human Settlement in Mau Forest
## Objectives
* To determine the impact of population growth on forest loss in Mau Forest,Narok County:Kenya.
* To Develop mathematical and statistical models to understand how population growth contributes to forest loss in Mau Forest over time.
* Develop mathematical and statistical models to understand how population growth contributes to forest loss in Mau Forest over time.
* Compare Differential Equation models with traditional statistical models.
* Demonstrate how mathematics can be used to model environmental change.
* To create a regression model to show the impact.
* To find out how differential equations is used in real-world problems.
* To create visualisations based on findings using R.
## Background on the Project
### Map of Mau Forest in Kenya
* I really struggled, still do, learning differential equations.
* I wanted to see how I can apply differential equations to projects since Calculus is a key Mathematical Foundation in Data Science.
* I recently did an assignment for my Sustainable Resource Management class (ENV2001) titled 'IMPACT OF POPULATION GROWTH AND HUMAN-INDUCED DEVELOPMENT ACTIVITIES ON ENVIRONMENTAL DEGRADATION:SUSTAINABLE APPROACHES AGAINST THE VICE GIVING RELEVANT EXAMPLES FROM MY COUNTRY'.
* The assignment focused on:Population growth, Human activities and Environmental degradation.
* I became excited on combining Mathematics, Environmental Studies and Statisticss.
* This is also my first math centered project so I am very excited.
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# 1)Mach …