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Table of contents
1 Introduction
1.1 Solar wind and the near-Earth environment
1.2 Large-scale solar events
1.3 The magnetopause, boundary between the solar wind and the magnetosphere
1.4 Small-scale physical processes of the near-Earth environment
1.5 Summary
1.6 Bibliography
2 Machine learning as an automatic selection tool
2.1 Introduction
2.2 Different types of supervised classification
2.3 Evaluating the performances of an algorithm
2.4 ImplementingMachine Learning
2.5 Machine Learning in space physics
2.6 Bibliography
3 An example of ambiguously labeled problem: automatic detection of ICMEs
3.1 Introduction
3.2 Interplanetary CoronalMass Ejections
3.3 Data
3.4 Algorithm
3.5 Results
3.6 Robustness
3.7 Global quality of the prediction
3.8 Conclusion
3.9 Bibliography
4 Automatic classification of the three near-Earth regions
4.1 Introduction
4.2 Data
4.3 Labeling THEMIS data
4.4 Algorithm selection
4.5 Algorithm performance
4.6 Adaptability of the model: from a mission to the other
4.7 Comparison withmanually set thresholds
4.8 Massive detection of boundary crossings
4.9 Conclusion
4.10 Bibliography
5 Statistical analysis of the magnetopause shape and location
5.1 Introduction
5.2 A brief insight on themagnetopause shape and location models
5.3 Statistical analysis of the magnetopause crossing
5.4 Fitting a new magnetopausemodel
5.5 Nature of the near-cusp magnetopause
5.6 Conclusion
5.7 Bibliography
6 Automatic detection of magnetopause plasma flow
6.1 Introduction
6.2 Construction of the dataset
6.3 Jet detection pipeline
6.4 Method performance
6.5 Adaptability of the method
6.6 Massive detection of magnetopause plasma jets
6.7 Conclusion
6.8 Bibliography
7 Conclusions and prespectives
7.1 Overview
7.2 Application of supervised machine learning algorithms
7.3 Position and shape of the magnetopause
7.4 Potential of machine learning algorithms and larger perspectives
A Coordinates systems I
A.1 Geocentric Solar Ecliptic (GSE)
A.2 Geocentric SolarMagnetospheric (GSM)
A.3 LocalMagnetopause Normal (LMN)
A.4 Magnetic Local Time (MLT)
B Additional prediction examples III
B.1 ICMEs
B.2 Near-Earth regions
B.3 Cusp external boundary
B.4 Reconnection jets
C List of Acronyms XV
