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A 5G-TSN joint resource scheduling algorithm based on optimized deep reinforcement learning model for industrial networks.

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Title: A 5G-TSN joint resource scheduling algorithm based on optimized deep reinforcement learning model for industrial networks.
Authors: Zhang, Yang1, Sun, Lei1, Ma, Zhangchao1, Wang, Jianquan1, Fu, Meixia1, Joung, Jinoo2
Source: Ad Hoc Networks; Apr2025, Vol. 170, pN.PAG-N.PAG, 1p
Database: Applied Science & Technology Source
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  Availability: 0
Header DbId: aci
DbLabel: Applied Science & Technology Source
An: 182977766
AccessLevel: 2
PubType: Academic Journal
PubTypeId: academicJournal
PreciseRelevancyScore: 0
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  Data: A 5G-TSN joint resource scheduling algorithm based on optimized deep reinforcement learning model for industrial networks.
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  Data: <searchLink fieldCode="JN" term="%22Ad+Hoc+Networks%22">Ad Hoc Networks</searchLink>; Apr2025, Vol. 170, pN.PAG-N.PAG, 1p
PLink https://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=aci&AN=182977766
RecordInfo BibRecord:
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      – Type: doi
        Value: 10.1016/j.adhoc.2025.103783
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      – Code: eng
        Text: English
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      – TitleFull: A 5G-TSN joint resource scheduling algorithm based on optimized deep reinforcement learning model for industrial networks.
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            NameFull: Zhang, Yang
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            NameFull: Sun, Lei
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            NameFull: Ma, Zhangchao
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            NameFull: Fu, Meixia
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            – D: 01
              M: 04
              Text: Apr2025
              Type: published
              Y: 2025
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              Value: 170
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