A Comparative Study of non-deep Learning, Deep Learning, and Ensemble Learning Methods for Sunspot Number Prediction-Reference-Cited by-同舟云学术

A Comparative Study of non-deep Learning, Deep Learning, and Ensemble Learning Methods for Sunspot Number Prediction

Published:2022-05-24 Issue:1 Volume:36 Page:
ISSN:0883-9514
Container-title:Applied Artificial Intelligence
language:en
Short-container-title:Applied Artificial Intelligence

Author:

Dang Yuchen¹,Chen Ziqi²,Li Heng³,Shu Hai⁴

Affiliation:

1. Center for Data Science, New York University, New York, New York, USA

2. Key Laboratory of Advanced Theory and Application in Statistics and Data Science-MOE, School of Statistics, East China Normal University, Shanghai, China

3. Department of Computer Science and Engineering, Southern University of Science and Technology, Shenzhen, Guangdong Province, China

4. Department of Biostatistics, School of Global Public Health, New York University, New York, USA

Funder

New York University

Publisher

Informa UK Limited

Subject

Artificial Intelligence

Link

https://www.tandfonline.com/doi/pdf/10.1080/08839514.2022.2074129

Reference82 articles.

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3. Sunspot Number Prediction Using Gated Recurrent Unit (GRU) Algorithm

4. Influence of geomagnetic activity and atmospheric pressure on human arterial pressure during the solar cycle 24

5. Beltagy, I., M. E. Peters, and A. Cohan. 2020. Longformer: The long-document transformer. arXiv preprint arXiv:2004.05150.

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