Citation

See, Thian Meng and Yogarayan, Sumendra and Abdul Razak, Siti Fatimah and Kannan, Subarmaniam and Azman, Afizan (2023) Advances of vehicular ad hoc network using machine learning approach. Indonesian Journal of Electrical Engineering and Computer Science, 32 (3). p. 1426. ISSN 2502-4752

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Abstract

Vehicular ad hoc networks (VANETs) play a crucial role in intelligent transportation systems (ITS), enabling seamless communication between vehicles and other entities. VANETs provide a wide range of services, allowing vehicles to communicate with each other and with roadside infrastructure. With the increasing amount of data generated by VANETs, machine learning approaches have emerged as valuable tools to address complex challenges in this domain. This paper presents a comprehensive literature review on the application of machine learning in VANETs. The paper discusses the potential challenges and future research directions in the field, emphasizing the need for more accessible machine learning solutions for VANETs. This review emphasizes the significant role of machine learning approach in advancing the capabilities of VANETs and shaping the future of intelligent transportation systems

Item Type:	Article
Uncontrolled Keywords:	Algorithm
Subjects:	Q Science > QA Mathematics > QA71-90 Instruments and machines > QA75.5-76.95 Electronic computers. Computer science
Divisions:	Faculty of Information Science and Technology (FIST)
Depositing User:	Ms Nurul Iqtiani Ahmad
Date Deposited:	02 Jan 2024 07:16
Last Modified:	02 Jan 2024 07:16
URII:	http://shdl.mmu.edu.my/id/eprint/11964

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