Incorporating Physical Knowledge Into Machine Learning for Planetary Space Physics

Incorporating Physical Knowledge Into Machine Learning for Planetary Space Physics

Recent improvements in data collection volume from planetary and space physics missions have allowed the application of novel data science techniques. The Cassini mission for example collected over 600 gigabytes of scientific data from 2004 to 2017. This represents a surge of data on the Saturn syst...

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Bibliographic Details
Main Authors: Abigail R. Azari, Jeffrey W. Lockhart, Michael W. Liemohn, Xianzhe Jia
Format: Article
Language:English
Published: Frontiers Media S.A. 2020-07-01
Series:Frontiers in Astronomy and Space Sciences
Subjects:
planetary science
automated event detection
space physics
Saturn
physics-informed machine learning
feature engineering
Online Access:https://www.frontiersin.org/article/10.3389/fspas.2020.00036/full

Internet

https://www.frontiersin.org/article/10.3389/fspas.2020.00036/full

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