Titlebook: Machine Learning for Networking; 4th International Co éric Renault,Selma Boumerdassi,Paul Mühlethaler Conference proceedings 2022 Springer

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書目名稱Machine Learning for Networking影響因子(影響力)




書目名稱Machine Learning for Networking影響因子(影響力)學(xué)科排名




書目名稱Machine Learning for Networking網(wǎng)絡(luò)公開度




書目名稱Machine Learning for Networking網(wǎng)絡(luò)公開度學(xué)科排名




書目名稱Machine Learning for Networking被引頻次




書目名稱Machine Learning for Networking被引頻次學(xué)科排名




書目名稱Machine Learning for Networking年度引用




書目名稱Machine Learning for Networking年度引用學(xué)科排名




書目名稱Machine Learning for Networking讀者反饋




書目名稱Machine Learning for Networking讀者反饋學(xué)科排名

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Conference proceedings 2022ris, France, in December 2021. The 10 revised full papers included in the volume were carefully reviewed and selected from 30 submissions. They present and discuss new trends in?in deep and reinforcement learning, pattern recognition and classification for networks, machine learning for network slic

鞭子

Evaluation of Machine Learning Methods for Image Classification: A Case Study of Facility Surface D methods. With these methods, accuracies of 98.6% and 96% were achieved for RC damage classification, respectively. The results of this study demonstrate that the use of machine learning can yield favorable results for damage image classification.

Chronic

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Distance Estimation Using LoRa and Neural Networks,al measurements that represent an actual search and rescue operation, we have achieved distance estimations (between 0 to 120?m) with less than 5% mean error. Add to this, our results, which are based on various LoRa radio parameters, show an improvement of 78% over the mechanisms that use RSSI as the only parameter.

Horizon

Conference proceedings 2022buted and decentralized machine learning algorithms, intelligent cloud-support communications, resource allocation, energy-aware communications, software-defined networks, cooperative networks, positioning and navigation systems, wireless communications, wireless sensor networks, and underwater sensor networks.

CLAMP

to several subvolumes which cover - in alphabetical order - all binary systems of importance. .Subvolume IV/5.H, the eighth of the series, deals with the systems Li-Mi ... Nd-Zr. Further subvolumes are in preparation.978-3-540-68538-8Series ISSN 1615-1844 Series E-ISSN 1616-9522

使堅(jiān)硬

Ching-Lung Fanto several subvolumes which cover - in alphabetical order - all binary systems of importance. .Subvolume IV/5.H, the eighth of the series, deals with the systems Li-Mi ... Nd-Zr. Further subvolumes are in preparation.978-3-540-68538-8Series ISSN 1615-1844 Series E-ISSN 1616-9522

受辱

Abdullah Alshra’a,Seitz Jochento several subvolumes which cover - in alphabetical order - all binary systems of importance. .Subvolume IV/5.H, the eighth of the series, deals with the systems Li-Mi ... Nd-Zr. Further subvolumes are in preparation.978-3-540-68538-8Series ISSN 1615-1844 Series E-ISSN 1616-9522