找回密碼
 To register

QQ登錄

只需一步,快速開(kāi)始

掃一掃,訪問(wèn)微社區(qū)

打印 上一主題 下一主題

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

[復(fù)制鏈接]
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
 關(guān)于派博傳思  派博傳思旗下網(wǎng)站  友情鏈接
派博傳思介紹 公司地理位置 論文服務(wù)流程 影響因子官網(wǎng) 吾愛(ài)論文網(wǎng) 大講堂 北京大學(xué) Oxford Uni. Harvard Uni.
發(fā)展歷史沿革 期刊點(diǎn)評(píng) 投稿經(jīng)驗(yàn)總結(jié) SCIENCEGARD IMPACTFACTOR 派博系數(shù) 清華大學(xué) Yale Uni. Stanford Uni.
QQ|Archiver|手機(jī)版|小黑屋| 派博傳思國(guó)際 ( 京公網(wǎng)安備110108008328) GMT+8, 2025-10-30 08:00
Copyright © 2001-2015 派博傳思   京公網(wǎng)安備110108008328 版權(quán)所有 All rights reserved
快速回復(fù) 返回頂部 返回列表
宁都县| 伊川县| 苍梧县| 定兴县| 新田县| 清远市| 宁南县| 吴川市| 新沂市| 银川市| 洛隆县| 鹤山市| 台中市| 德钦县| 修水县| 永善县| 洪泽县| 滨州市| 比如县| 武川县| 新津县| 娱乐| 启东市| 垫江县| 博客| 大兴区| 安庆市| 万源市| 深水埗区| 夏邑县| 雅安市| 班戈县| 尖扎县| 河北省| 牙克石市| 甘南县| 金湖县| 溧阳市| 固镇县| 修水县| 广昌县|