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A New Method for Optimizing Low-Earth-Orbit Satellite Communication Links Based on Deep Reinforcement Learning.

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Title: A New Method for Optimizing Low-Earth-Orbit Satellite Communication Links Based on Deep Reinforcement Learning.
Authors: Yu, He1, 13261059095@163.com, Li, Shengli1, Wu, Junchao1, Sun, Yanhong1, Wang, Limin1
Source: Aerospace (MDPI Publishing); Mar2026, Vol. 13 Issue 3, p285, 19p
Database: Applied Science & Technology Source
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  Availability: 0
Header DbId: aci
DbLabel: Applied Science & Technology Source
An: 192642434
AccessLevel: 2
PubType: Academic Journal
PubTypeId: academicJournal
PreciseRelevancyScore: 0
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  Data: A New Method for Optimizing Low-Earth-Orbit Satellite Communication Links Based on Deep Reinforcement Learning.
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  Data: <searchLink fieldCode="JN" term="%22Aerospace+%28MDPI+Publishing%29%22">Aerospace (MDPI Publishing)</searchLink>; Mar2026, Vol. 13 Issue 3, p285, 19p
PLink https://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=aci&AN=192642434
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        Value: 10.3390/aerospace13030285
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      – Code: eng
        Text: English
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        PageCount: 19
        StartPage: 285
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      – TitleFull: A New Method for Optimizing Low-Earth-Orbit Satellite Communication Links Based on Deep Reinforcement Learning.
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            NameFull: Li, Shengli
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              Text: Mar2026
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              Y: 2026
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              Value: 13
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