在KASCADE数据上使用现代机器学习方法进行推广和教育

V. Tokareva, D. Kostunin, I. Plokhikh, V. Sotnikov
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引用次数: 0

摘要

现代天体粒子物理学将机器学习方法广泛应用于噪声抑制、图像识别、事件分类等问题。当使用这些方法时,除了获得新的科学知识外,利用它们的教育潜力也很重要。在这项工作中,我们展示了我们创建的基于机器学习的应用程序的演示版本,这有助于学生和更广泛的受众更加熟悉宇宙射线物理学,并展示了如何使用机器学习方法来分析数据。该工作讨论了扩展应用程序的功能和方法方法的前景,以开发互动推广材料在这一领域。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Using Modern Machine Learning Methods on KASCADE Data for Outreach and Education
Modern astroparticle physics makes wide use of machine learning methods in such problems as noise suppression, image recognition, event classification. When using these methods, in addition to obtaining new scientific knowledge, it is important also to take advantage of their educational potential. In this work we present a demo version of the machine-learning based application we have created, which helps students and a broader audience to get more familiar with the cosmic ray physics, and shows how machine learning methods can be used to analyze data. The work discusses the prospects for expanding the application’s functionality and methodological approaches to the development of interactive outreach materials in this area.
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