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Title:

Apply noise filters for better forecast performance in Machine Learning

Document type:
Konferenzbeitrag
Contribution type:
Vortrag / Präsentation
Author(s):
Le N., Männel B., Natras R., Sakic P., Deng Z., Schuh H.
Abstract:
In Machine Learning (ML), one of the crucial tasks is understanding data characteristics to be able to extract exactly relevant information, while noise contained in data can cause misleading estimations and decrease the generalizability of ML-based prediction models. So far, only few previous studies have applied noise filtering techniques when building forecast models. Hence, their efficiency on ML-based forecasts has not yet been comprehensively demonstrated. Therefore, we aim to determine op...     »
Keywords:
Machine Learning, Noise filters, Savitzky Golay filter, TEC forecast, Crustal motion, Earth’s polar motion
Book / Congress title:
European Geosciences Union (EGU) General Assembly
Date of congress:
2022-05-23 - 2022-05-27
Year:
2022
Year / month:
2022-05
Fulltext / DOI:
doi:https://doi.org/10.5194/egusphere-egu22-4039
WWW:
https://meetingorganizer.copernicus.org/EGU22/EGU22-4039.html
TUM Institution:
Deutsches Geodätisches Forschungsinstitut (DGFI-TUM)
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