NORMA eResearch @NCI Library

A Machine Learning Based Approach to Predict Species-Habitat Relationship in Australia

Belur Ramesh, Preethi (2023) A Machine Learning Based Approach to Predict Species-Habitat Relationship in Australia. Masters thesis, Dublin, National College of Ireland.

[thumbnail of Master of Science]
PDF (Master of Science)
Download (2MB) | Preview
[thumbnail of Configuration manual]
PDF (Configuration manual)
Download (3MB) | Preview


The ecological balance hangs on the abundance of flora and fauna. The declining numbers of species can be attributed to multiple reasons such as climate change, habitat destruction and human interference. Therefore, this research aims to represent the relationship between the species and the climatic conditions of the habitat using Machine Learning Techniques and Statistical Analysis to understand the climatic conditions affecting the distribution patterns of the endemic species of Australia. As a novel approach, this research also tries to draw parallels between the warm-blooded bird species and cold blooded frog species to infer if species that inherently react differently to the climate show similar signs of decline and distribution to historic and future climate variables.

Item Type: Thesis (Masters)
Agarwal, Bharat
Subjects: Q Science > QA Mathematics > Electronic computers. Computer science
T Technology > T Technology (General) > Information Technology > Electronic computers. Computer science
Q Science > QL Zoology
Q Science > Q Science (General) > Self-organizing systems. Conscious automata > Machine learning
Divisions: School of Computing > Master of Science in Data Analytics
Depositing User: Tamara Malone
Date Deposited: 17 May 2023 11:07
Last Modified: 17 May 2023 11:07

Actions (login required)

View Item View Item