0000-0001-5983-1149

100001224

100001363

10614331

23567970800

26395

34939

56061499600

60380549

Kitamura, Kentaro

Saita, Satoko

Teramoto, Mariko

北村, 健太郎

寺本, 万里子

才田, 聡子

English

Kyutacar : Kyushu Institute of Technology Academic Repository

R011-02C会場：9/27　AM1（9:00-10:30）9:15～9:30#才田　聡子 1),寺本　万里子 2),北村　健太郎 3)(1 北九州高専,(2 九工大,(3 九州工大Classification of Satellite-Obtained Time Series Data: A Comparative Study ofRule-Based and Machine-Learning Approaches#Satoko Saita1),Mariko Teramoto2),Kentarou Kitamura3)(1National Institute of Technology, Kitakyushu College,(2Kyushu Institute of Technology,(3Kyushu Institute of TechnologyDue to communication volume constraints, nanosatellites conducting scientific observations must reduce downlink datathrough onboard data preprocessing. Therefore, we conducted a study to classify time series data of the geomagnetic fieldobtained from the SWARM satellite, aiming to determine the most suitable onboard classification method for phenomenain the geomagnetic field. We employed rule-based, K-means, and combined CNN methods for the classifications. Theexperimental results clearly demonstrated the effectiveness of the machine-learning model with LSTM networks.

Classification of Satellite-Obtained Time Series Data: A Comparative Study of Rule-Based and Machine-Learning Approaches

https://kyutech.repo.nii.ac.jp/record/2001587/files/2023_DC08_4.pdf

Classification of Satellite-Obtained Time Series Data: A Comparative Study of Rule-Based and Machine-Learning Approaches

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Kyutacar : Kyushu Institute of Technology Academic Repository