Selective Tensorized Multi-layer LSTM for Orbit Prediction-Reference-Cited by-同舟云学术

Selective Tensorized Multi-layer LSTM for Orbit Prediction

Published:2022-10-17 Issue: Volume: Page:
ISSN:
Container-title:Proceedings of the 31st ACM International Conference on Information & Knowledge Management
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Author:

Shin Youjin¹,Park Eun-Ju²,Woo Simon S.²,Jung Okchul³,Chung Daewon³

Affiliation:

1. Sejong University, Seoul, Republic of Korea

2. Sungkyunkwan University, Suwon, Republic of Korea

3. Korea Aerospace Research Institute (KARI), Daejeon, Republic of Korea

Publisher

ACM

Link

https://dl.acm.org/doi/pdf/10.1145/3511808.3557138

Reference40 articles.

1. Lars Buitinck , Gilles Louppe , Mathieu Blondel , Fabian Pedregosa , Andreas Mueller , Olivier Grisel , Vlad Niculae , Peter Prettenhofer , Alexandre Gramfort , Jaques Grobler , Robert Layton , Jake VanderPlas , Arnaud Joly , Brian Holt , and Gaël Varoquaux . 2013 . API design for machine learning software: experiences from the scikit-learn project . In ECML PKDD Workshop: Languages for Data Mining and Machine Learning. 108--122 . Lars Buitinck, Gilles Louppe, Mathieu Blondel, Fabian Pedregosa, Andreas Mueller, Olivier Grisel, Vlad Niculae, Peter Prettenhofer, Alexandre Gramfort, Jaques Grobler, Robert Layton, Jake VanderPlas, Arnaud Joly, Brian Holt, and Gaël Varoquaux. 2013. API design for machine learning software: experiences from the scikit-learn project. In ECML PKDD Workshop: Languages for Data Mining and Machine Learning. 108--122.

2. Rigorous analysis on performance of LEO satellite ground station in urban environment

3. Analysis of individual differences in multidimensional scaling via an n-way generalization of “Eckart-Young” decomposition

4. XGBoost

5. Prediction of Satellite Time Series Data Based on Long Short Term Memory-Autoregressive Integrated Moving Average Model (LSTM-ARIMA)

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