… In this section, we present the state of the art on machine learning solutions proposed for
VANETs to improve their performance. Our search for related proposals has been focused on …

… literature review on the application of machine learning in VANETs. The paper … machine
learning solutions for VANETs. This review emphasizes the significant role of machine learning …

… aspects in autonomous driving in vehicular ad-hoc networks. The conventional techniques
… To address this issue, this paper proposed a machine learning method based on stochastic …

… Then, while working with multi- class data, we develop a novel approach to solving the
problem of learning from imbalanced data. Finally, we test multiple machine learning classifiers to …

… We show that it is possible to pose a coarse-grained localization problem as a discriminative
classification problem that can be solved using tools from the statistical machine learning …

… In this paper, we propose extreme learning machines (ELMs), known for universal
approximation, to model and predict mobility of arbitrary nodes in a mobile ad hoc network (MANET). …

… of Ad hoc network in … machine learning algorithm is developed to improve the accuracy.
Specifically, we propose a DV-Hop self-localization algorithm using extreme learning machine (…

… In ad hoc networks, non-linear machine learning techniques such as SVM were infeasible …
made combining cross layer schemes and non-linear machine learning techniques infeasible. …

… The vehicular ad-hoc network (VANET) is a new subcategory of mobile ad-hoc networks that
has … In this paper, a multi-level Intrusion Detection System based on Machine Learning (ML) …

… Vehicular ad hoc networks (VANETs) are recent advancements that permit vehicles to …
In this paper, an efficient machine learning (ML) model is developed to identify the impact of …