论文标题
在线学习到航天器内存转储优化的应用
An Application of Online Learning to Spacecraft Memory Dump Optimization
论文作者
论文摘要
在本文中，我们向空间操作领域的专家建议介绍了在线学习的现实应用，并对来自哥白尼Sentinel-6卫星的现实生活数据进行了测试。我们表明，与传统技术相比，在航天器存储器库优化的优化中，一种轻巧的跟随算法会导致性能增长超过$ 60 \％$。
In this paper, we present a real-world application of online learning with expert advice to the field of Space Operations, testing our theory on real-life data coming from the Copernicus Sentinel-6 satellite. We show that in Spacecraft Memory Dump Optimization, a lightweight Follow-The-Leader algorithm leads to an increase in performance of over $60\%$ when compared to traditional techniques.
