Document Type
Honors Thesis
Publication Date
Spring 2015
Abstract
The purpose of this research is to investigate the potential of applying concepts from ma- chine learning, such as pattern recognition and matching, to detect climatic signals in ice core data. The main components of this project are the development of a pattern language for expressing relationships between chemical signals over time, a method of tokenizing ice core chemistry data into an easily manageable form, a method of matching specific instances of climatic signals to a specific pattern string, and a method to recognize and evaluate patterns within ice core chemistry data. While there are weaknesses in each of these components, this research serves as a successful proof of concept for the feasibility of applying machine learning techniques to ice core analysis.
Recommended Citation
Dunn, Nathan, "Pattern Recognition and Matching in Ice Core Data" (2015). Honors College. 224.
https://digitalcommons.library.umaine.edu/honors/224