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Titlebook: Quality, Reliability, Security and Robustness in Heterogeneous Systems; 13th International C Lei Wang,Tie Qiu,Wenbing Zhao Conference proce

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書(shū)目名稱Quality, Reliability, Security and Robustness in Heterogeneous Systems
副標(biāo)題13th International C
編輯Lei Wang,Tie Qiu,Wenbing Zhao
視頻videohttp://file.papertrans.cn/781/780409/780409.mp4
叢書(shū)名稱Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engi
圖書(shū)封面Titlebook: Quality, Reliability, Security and Robustness in Heterogeneous Systems; 13th International C Lei Wang,Tie Qiu,Wenbing Zhao Conference proce
描述This book constitutes the refereed post-conference proceedings of the 13.th.?International Conference on Quality, Reliability, Security and Robustness in Heterogeneous Networks, QShine 2017, held in Dalian, China, in December 2017. The 25 revised full papers were carefully reviewed and selected from 43 submissions. The papers are organized thematically in tracks, starting with mobile and wireless networks, quality and reliability, wireless networking algorithms and protocols, and smart applications.
出版日期Conference proceedings 2018
關(guān)鍵詞wireless telecommunication systems; computer networks; telecommunication networks; wireless sensor netw
版次1
doihttps://doi.org/10.1007/978-3-319-78078-8
isbn_softcover978-3-319-78077-1
isbn_ebook978-3-319-78078-8Series ISSN 1867-8211 Series E-ISSN 1867-822X
issn_series 1867-8211
copyrightICST Institute for Computer Sciences, Social Informatics and Telecommunications Engineering 2018
The information of publication is updating

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Community Preserving Sign Prediction for Weak Ties of Complex Networks are firstly divided into different communities. The weak ties are then detected via the connections of the divided communities. SVM classifier is finally trained and used to predict the sign of weak ties. Experiments held on the real world dataset verify the high prediction performances of our proposed method for weak ties of complex networks.
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Lake-Level Prediction Leveraging Deep Neural Networkmature machine learning methods, namely Multiple Linear Regression (MLR) and Artificial Neural Network (ANN), are also adopted for the comparison purpose. The result shows that the DL model preforms the best on three criteria, following by the three-layered Back-Propagation ANN model and MLR model.
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Conference proceedings 2018 43 submissions. The papers are organized thematically in tracks, starting with mobile and wireless networks, quality and reliability, wireless networking algorithms and protocols, and smart applications.
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