Titlebook: Developing Networks using Artificial Intelligence; Haipeng Yao,Chunxiao Jiang,Yi Qian Book 2019 Springer Nature Switzerland AG 2019 machin

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書目名稱Developing Networks using Artificial Intelligence影響因子(影響力)




書目名稱Developing Networks using Artificial Intelligence影響因子(影響力)學(xué)科排名




書目名稱Developing Networks using Artificial Intelligence網(wǎng)絡(luò)公開度




書目名稱Developing Networks using Artificial Intelligence網(wǎng)絡(luò)公開度學(xué)科排名




書目名稱Developing Networks using Artificial Intelligence被引頻次




書目名稱Developing Networks using Artificial Intelligence被引頻次學(xué)科排名




書目名稱Developing Networks using Artificial Intelligence年度引用




書目名稱Developing Networks using Artificial Intelligence年度引用學(xué)科排名




書目名稱Developing Networks using Artificial Intelligence讀者反饋




書目名稱Developing Networks using Artificial Intelligence讀者反饋學(xué)科排名

膽小懦夫

Zu G.s geologischer Forschung nach 1800djustment of network traffic distribution, increase detection accuracy and reduce the false negative rate. Finally, we propose an end-to-end IoT traffic classification method relying on deep learning aided capsule network for the sake of forming an efficient classification mechanism that integrates

鑒賞家

波動

Zu G.s geologischer Forschung nach 1800 system. We firstly propose an effective model for the similarity metrics of English sentences. In the model, we first make use of word embedding and convolutional neural network (CNN) to produce a sentence vector and then leverage the information of the sentence vector pair to calculate the score o

符合國情

植物茂盛

植物茂盛

Intelligent Network Control, and propose a novel Quality of Service (QoS) enabled load scheduling algorithm based on reinforcement learning to solve the problem of complexity and pre-strategy in the networks. In addition, we present a Wireless Local Area Networks (WLAN) interference self-optimization method based on a Self-Org

TRACE

Intention Based Networking Management, system. We firstly propose an effective model for the similarity metrics of English sentences. In the model, we first make use of word embedding and convolutional neural network (CNN) to produce a sentence vector and then leverage the information of the sentence vector pair to calculate the score o

外形

Conclusions and Future Challenges, becomes substantially important to strengthen the management of data traffic in networks. As a critical part of massive data analysis, traffic awareness plays an important role in ensuring network security and defending traffic attacks. Moreover, the classification of different traffic can help to

亞當(dāng)心理陰影

Book 2019pproaches for self-learning control strategies are introduced. In addition, resource management problems are ubiquitous in the networking field, such as job scheduling, bitrate adaptation in video streaming and virtual machine placement in cloud computing. Compared with the traditional with-box appr