Multivariate Gaussian Mixture-based Prediction Model for Opportunistic Networks-Reference-Cited by-同舟云学术

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Multivariate Gaussian Mixture-based Prediction Model for Opportunistic Networks

Published:2022-05-16 Issue: Volume: Page:
ISSN:
Container-title:ICC 2022 - IEEE International Conference on Communications
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Author:

Singh Jagdeep¹,Dhurandher Sanjay Kumar²,Woungang Isaac³,Chatzimisios Periklis⁴

Affiliation:

1. Sant Longowal Institute of Engineering and Technology,Department of Computer Science and Engineering,Longowal,Punjab,India

2. Netaji Subhas University of Technology,Department of Information Technology,New Delhi,India

3. Ryerson University,Department of Computer Science,Toronto,ON,Canada

4. International Hellenic University,Greece

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/9837954/9838246/09838475.pdf?arnumber=9838475

Reference30 articles.

1. CRAWDAD dataset cambridge/haggle (v. 2009-05-29);scott;CRAWDAD Wireless Network Data Archive,2009

2. A robust EM clustering algorithm for Gaussian mixture models

3. Gaussian Mixture Models

4. GMMR: A Gaussian mixture model based unsupervised machine learning approach for optimal routing in opportunistic IoT networks

5. Contract Theory based Incentive Design Mechanism for Opportunistic IoT Networks

Cited by 2 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. SCON: A Secure Cooperative Framework Against Gossip Dissemination in Opportunistic Network;2023 IEEE Symposium on Computers and Communications (ISCC);2023-07-09

2. Reinforcement Learning Based Congestion Control Mechanism for Opportunistic Networks;2022 IEEE Globecom Workshops (GC Wkshps);2022-12-04

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