Title (PDF)

Machine Learning in Space Weather: Forecasting, Identification & Uncertainty Quantification.


The study of variations in the space environment between the Sun and the Earth constitutes the core of space weather research. Plasma ejected by the Sun couples with the Earth’s magnetic field in complex ways that determine the state of the Earth’s magnetosphere. Adverse effects from space weather can impact communication networks, power grids and lo- gistics infrastructure, all crucial pillars of a civilization that is reliant on technology.

It is important to use data sources, scientific knowledge and statistical techniques to create space weather forecasting and monitoring systems of the future. This thesis aims to be a step towards that goal.


    title = "Machine learning in space weather: forecasting, identification & uncertainty quantification",
    author = "Chandorkar, {Mandar Hemant}",
    note = "Proefschrift",
    year = "2019",
    month = nov,
    day = "14",
    language = "English",
    isbn = "978-90-386-4903-0",
    publisher = "Technische Universiteit Eindhoven",
    school = "Department of Applied Physics"