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Updated: Jul 20, 2025

Surface Mapping of Earth-like Exoplanets using Single Point Light Curves
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使用支持矢量机 (SVM) 和长短期存储器 (LSTM) 进行低地球轨道 (LEO) 居住空间物体 (RSO) 光曲线的分类

Randa Qashoa1, Regina Lee1

  • 1Department of Earth and Space Science, York University, Toronto, ON M3J 1P3, Canada.

Sensors (Basel, Switzerland)
|July 29, 2023
PubMed
概括

这项研究引入了一种新方法,用于使用光曲线数据对低地球轨道 (LEO) 居住空间物体 (RSO) 进行分类. 使用长短期记忆 (LSTM) 的深度学习实现了92%的准确性,超过了传统的机器学习.

关键词:
空间 情境意识 空间 情境意识光线曲线的光线曲线长期短期记忆 长期短期记忆在低地球轨道上运行.居住空间对象的空间对象支持矢量机器的支持矢量机器.

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