Research Article
Machine Learning Techniques for Particle Classification in Microphysics
@INPROCEEDINGS{10.4108/eai.21-11-2024.2354579, author={Zeyu Yang and Deshui He}, title={Machine Learning Techniques for Particle Classification in Microphysics}, proceedings={Proceedings of the 2nd International Conference on Machine Learning and Automation, CONF-MLA 2024, November 21, 2024, Adana, Turkey}, publisher={EAI}, proceedings_a={CONF-MLA}, year={2025}, month={3}, keywords={decision trees neural networks physics particle classification machine learning regression}, doi={10.4108/eai.21-11-2024.2354579} }- Zeyu Yang
Deshui He
Year: 2025
Machine Learning Techniques for Particle Classification in Microphysics
CONF-MLA
EAI
DOI: 10.4108/eai.21-11-2024.2354579
Abstract
This study proposes various machine learning methods for classifying physical particles including protons, pions, kaons, and D mesons in microphysics. The research group evaluated the performance of decision trees, neural networks, traditional methods, et cetera. showing that Decision Trees are better than other methods in terms of the mean square error and the accuracy of the final classification. This indicates that the decision tree may provide certain data features and is an outstanding and feasible approach in this field. The last achieved accuracy was 65 % for the global range and 73% for the local range. Thus, it can be a good way to improve particle classification by combining traditional and machine learning methods.
