Coastline Prediction Using Climate Change Models
The rise in sea levels is one of the most significant consequences of global warming, with countries such as the Netherlands facing the threat of submersion within the next century. The melting of glaciers caused by the increase in carbon dioxide levels and resulting rise in global temperatures is contributing to the worldwide sea level rise. To better understand the factors affecting this increase, we collected and analyzed data, fitting it to a certain function to make predictions for future sea levels. The Root Mean Square Error (RMSE) was used to assess the standard deviation of the prediction errors between predicted and actual values. Additionally, a correlation matrix was used to assess the consistency of the data with each other. This study utilized curve fitting and machine learning methods to better predict and understand the rise in sea levels, which will help us take proactive steps to mitigate its impact.
I would like to express my gratitude to the students of the Intelligent Control Systems course of the YTÜ Control and Automation Engineering department, Class of Fall 2022, whose dedication and hard work made this project possible. I am also deeply thankful to Doctors Marco Rossi, Julia Hoerner, and Melda Ulusoy for their invaluable contributions.