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Titlebook: Emerging Networking Architecture and Technologies; First International Wei Quan Conference proceedings 2023 The Editor(s) (if applicable)

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樓主: burgeon
41#
發(fā)表于 2025-3-28 16:33:53 | 只看該作者
42#
發(fā)表于 2025-3-28 19:25:56 | 只看該作者
Emerging Networking Architecture and Technologies978-981-19-9697-9Series ISSN 1865-0929 Series E-ISSN 1865-0937
43#
發(fā)表于 2025-3-29 02:58:52 | 只看該作者
44#
發(fā)表于 2025-3-29 06:47:29 | 只看該作者
45#
發(fā)表于 2025-3-29 08:14:26 | 只看該作者
Conference proceedings 2023ld in? Shenzhen, China, in October 2022..The 50 papers presented were thoroughly reviewed and selected from the 106 submissions. The volume focuses?on the latest achievements in the field of emerging network technologies, covering the topics of emerging networking architecture, network frontier tech
46#
發(fā)表于 2025-3-29 15:22:45 | 只看該作者
47#
發(fā)表于 2025-3-29 16:15:17 | 只看該作者
H. Müller-Braunschweig,W.-Eberhard Mehlingge, a multi-agent deep reinforcement learning based algorithm is proposed for each resource provider to optimize its pricing strategy based on the environment information. Finally, extensive simulations have been performed to demonstrate the excellent performance of the proposed algorithm.
48#
發(fā)表于 2025-3-29 23:28:38 | 只看該作者
,Morphologie der Flie?gew?sser, which is used to identify the same video with different formats. Compared with the traditional approach, the proposed scheme can both ensure the integrity of the moderation data and reduce the total computation overhead.
49#
發(fā)表于 2025-3-30 00:36:03 | 只看該作者
Multi-agent Deep Reinforcement Learning-based Incentive Mechanism For Computing Power Networkge, a multi-agent deep reinforcement learning based algorithm is proposed for each resource provider to optimize its pricing strategy based on the environment information. Finally, extensive simulations have been performed to demonstrate the excellent performance of the proposed algorithm.
50#
發(fā)表于 2025-3-30 07:45:59 | 只看該作者
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