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Titel:

Apply noise filters for better forecast performance in Machine Learning

Dokumenttyp:
Konferenzbeitrag
Art des Konferenzbeitrags:
Vortrag / Präsentation
Autor(en):
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...     »
Stichworte:
Machine Learning, Noise filters, Savitzky Golay filter, TEC forecast, Crustal motion, Earth’s polar motion
Kongress- / Buchtitel:
European Geosciences Union (EGU) General Assembly
Datum der Konferenz:
2022-05-23 - 2022-05-27
Jahr:
2022
Jahr / Monat:
2022-05
Volltext / DOI:
doi:https://doi.org/10.5194/egusphere-egu22-4039
WWW:
https://meetingorganizer.copernicus.org/EGU22/EGU22-4039.html
TUM Einrichtung:
Deutsches Geodätisches Forschungsinstitut (DGFI-TUM)
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