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As a forerunner of space applications and the foundation of national space security, space science is entering a new phase characterized by "data explosion, multi−scale coupling, and prominent strategic demands." Traditional research paradigms struggle to address core challenges such as exponential data growth, complex system coupling, autonomous decision−making in deep space exploration, and real−time accurate space weather forecasting. The AI for Science (AI4S) paradigm has emerged as a revolutionary tool for this field, leveraging technologies including deep learning, physics−informed neural networks (PINNs), and causal inference. This paper systematically summarizes the remarkable domestic and international research progress in space science intelligent detection, intelligent recognition, in−depth exploration of mechanisms, and major application practices. It conducts an in−depth analysis of three core challenges: Data infrastructure construction, mechanism−causal modeling, and the implementation of data−intelligent applications. Key solutions such as standardized data governance, physical constraint integration and hybrid modeling, and model light weighting are proposed. Research shows that AI4S has driven a fundamental transformation of space science from "empirical statistics and post−hoc interpretation" to "data−physics collaborative modeling and cognition−driven research." Notable breakthroughs have been achieved globally in on−board intelligent deployment, high−precision planetary landform recognition, and full−chain space weather forecasting. The emergence of several domain−specific large models marks AI4S's entry into a stage of large−scale application in space science. This paper also looks forward to future development trends, laying a solid technological foundation for breakthroughs in space science innovation, support for major space missions, and national space security.
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| 科 Family | 属数 Number of genus | 种数 Number of species | 占总种数比例 Percentage of total species (%) | 属 Genus | 种数 Number of species | 占总种数比例 Percentage of total species (%) |
|---|---|---|---|---|---|---|
| 鹅膏菌科Amanitaceae | 2 | 11 | 5.26 | 鹅膏菌属 Amanita | 10 | 4.78 |
| 小菇科 Mycenaceae | 2 | 12 | 5.74 | 丝盖伞属 Inocybe | 5 | 2.39 |
| 多孔菌科 Polyporaceae | 8 | 14 | 6.70 | 蜡蘑属 Laccaria | 5 | 2.39 |
| 红菇科 Russulaceae | 3 | 23 | 11.00 | 小皮伞属 Marasmius | 6 | 2.87 |
| 小菇属 Mycena | 11 | 5.26 | ||||
| 光柄菇属 Pluteus | 5 | 2.39 | ||||
| 红菇属 Russula | 17 | 8.13 | ||||
| 栓菌属 Trametes | 5 | 2.39 |
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