Data and intelligent driven space science experimental research: New exploration under AI4S paradigm

Authors

Shengyang LI, Technology and Engineering Center for Space Utilization, Chinese Academy of Sciences, Beijing 100094, China; Key Laboratory of Space Utilization, Chinese Academy of Sciences, Beijing 100094, China; School of Aeronautics and Astronautics, University of Chinese Academy of Sciences, Beijing 100049, ChinaFollow
Kang LIU, Technology and Engineering Center for Space Utilization, Chinese Academy of Sciences, Beijing 100094, China; Key Laboratory of Space Utilization, Chinese Academy of Sciences, Beijing 100094, China; School of Aeronautics and Astronautics, University of Chinese Academy of Sciences, Beijing 100049, China
Yunfei LIU, Technology and Engineering Center for Space Utilization, Chinese Academy of Sciences, Beijing 100094, China; Key Laboratory of Space Utilization, Chinese Academy of Sciences, Beijing 100094, China; School of Aeronautics and Astronautics, University of Chinese Academy of Sciences, Beijing 100049, China
Chufan LAI, Technology and Engineering Center for Space Utilization, Chinese Academy of Sciences, Beijing 100094, China; Key Laboratory of Space Utilization, Chinese Academy of Sciences, Beijing 100094, China

Keywords

space science experiment data and intelligence driven artificial intelligence

Document Type

Disciplinary Development

Abstract

As artificial intelligence (AI) technology continues to advance, it is revolutionizing various scientific fields, giving rise to a new research paradigm known as AI for Science (AI4S). This study highlights the unique multidisciplinary advantages of AI in space science experiments conducted under microgravity conditions. It provides a comprehensive analysis of AI-driven approaches to multimodal space science experiment data pattern mining, domain knowledge extraction, interdisciplinary knowledge integration, and cognitive intelligence. The study reveals AI’s substantial potential to enhance intelligent scientific research, cognition, and discovery within the realm of space science experiments. The findings suggest that data-driven space science research, as a pivotal domain of AI4S, will significantly contribute to the development and innovation of space science experiment data ecosystems, advance AI4S research, and foster the growth of relevant scientific disciplines.

First page

371

Last Page

379

Language

Chinese

Publisher

Bulletin of Chinese Academy of Sciences

References

1 李国杰. 智能化科研（AI4R）: 第五科研范式. 中国科学院院刊, 2024, 39(1):1-9.Li G J. AI4R: The fifth scientific research paradigm. Bulletin of Chinese Academy of Sciences, 2024, 39(1): 1-9 (in Chinese)

2 鄂维南. AI 助力打造科学研究新范式. 中国科学院院刊, 2024, 39(1): 10-16. E W N. AI helps to establish a new paradigm for scientific research. Bulletin of Chinese Academy of Sciences, 2024, 39 (1): 10-16. (in Chinese)

3 Hey T, Tansley S, Tolle K, et al. The Fourth Paradigm: DataIntensive Scientific Discovery. Redmond: Microsoft Research, 2009.

4 顾逸东. 关于空间科学发展的一些思考. 中国科学院院刊, 2022, 37(8): 1031-1049. Gu Y D. Thoughts on space science development. Bulletin of Chinese Academy of Sciences, 2022, 37(8): 1031-1049. (in Chinese)

5 刘泽康. 空间站应用与发展阶段开年提速. 国际太空, 2023, (9):4-8. Liu Z K. Space station applications and development stages accelerate at the beginning of the year. Space International, 2023, (9): 4-8. (in Chinese)

6 顾逸东, 高铭, 赵光恒. 2022—2032 年中国空间站运行期科研利用规划. 空间科学学报, 2020, 40(5): 609-614. Gu Y D, Gao M, Zhao G H. Science research and utilization planning of China’s Space Station in operation period 2022-2032. Chinese Journal of Space Science, 2020, 40(5): 609-614. (in Chinese)

7 Zhang C, Yang Z, He X, et al. Multimodal intelligence: Representation learning, information fusion, and applications. IEEE Journal of Selected Topics in Signal Processing. 2020, 3(14): 478-493.

8 Elsinga G E, Scarano F, Wieneke B, et al. Tomographic particle image velocimetry. Experiments in Fluids, 2006, 41 (6): 933-947.

9 Matía I, González-Camacho F, Marco R, et al. Nucleolar structure and proliferation activity of Arabidopsis root cells from seedlings germinated on the International Space Station. Advances in Space Research, 2005, 36(7): 1244-1253.

10 Horio M. Overview of fluidization science and fluidized bed technologies// Scala F, ed. Fluidized Bed Technologies for Near-Zero Emission Combustion and Gasification. Cambridge: Woodhead Publishing, 2013: 3-41.

Recommended Citation

LI, Shengyang; LIU, Kang; LIU, Yunfei; and LAI, Chufan (2024) "Data and intelligent driven space science experimental research: New exploration under AI4S paradigm," Bulletin of Chinese Academy of Sciences (Chinese Version): Vol. 40 : Iss. 2 , Article 14.
DOI: https://doi.org/10.16418/j.issn.1000-3045.20240709003
Available at: https://bulletinofcas.researchcommons.org/journal/vol40/iss2/14