A Versatile Machine Learning-Based Vehicle-to-Vehicle Connectivity Model-Reference-Cited by-同舟云学术

A Versatile Machine Learning-Based Vehicle-to-Vehicle Connectivity Model

Published:2023-06-21 Issue: Volume: Page:
ISSN:
Container-title:2023 19th International Conference on Wireless and Mobile Computing, Networking and Communications (WiMob)
language:
Short-container-title:

Author:

Tahat Ashraf¹,Edwan Talal A.²,Dababseh Motaz-Bellah¹,Nidal Mohammed¹,Rumman Mohammed¹,Arabiat Alaa¹

Affiliation:

1. Princess Sumaya University for Technology,Department of Communications Engineering,Amman,Jordan

2. University of Jordan,Department of Computer Enginering,Amman,Jordan

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/10187718/10187720/10187740.pdf?arnumber=10187740

Reference26 articles.

1. An evaluation of machine learning algorithms inan experimental structural health monitoring system incorporating LoRa IoT connectivity;tahat;Proc IEEE International Instrumentation and Measurement Technology Conference,2022

2. A UHF Path Loss Model Using Learning Machine for Heterogeneous Networks

3. Understanding Machine Learning

4. A Distribution-Free Theory of Nonparametric Regression

5. Simplistic Machine Learning-Based Air-to-Ground Path Loss Modeling in an Urban Environment

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. An Exemplification of Decisions of Machine Learning Classifiers to Predict Handover in a 5G/4G/3G Cellular Communications Network;2024 20th International Conference on the Design of Reliable Communication Networks (DRCN);2024-05-06

2. On the Accuracy and Efficiency of Received Signal Strength Modelling for a Forest Environment;2024 IEEE International Conference on Machine Learning for Communication and Networking (ICMLCN);2024-05-05