… Ad-hoc Networks (MANET) and proposes a new method for detecting and preventing attacks
using machine learning. … the simulations, and a machine-learning model was designed to …

… In this work, we consider machine learning model with appropriate simulator based on its …
Develop Machine Learning model for providing vehicular framework for reducing the road …

… methods based on machine learning could potentially … adhoc networks as a multi-agent
learning domain and discuss some motivations for this study. We apply reinforcement learning …

… In this section we review some of the popular basic Machine Learning (basic ML) techniques
which include supervised, unsupervised, semi-supervised and reinforcement [9]. We …

… This paper presents a machine learning (ML) algorithm for recognition and low-cost tracking
of unknown spatially correlated signals using sensor readings in ad-hoc wireless sensor …

… EXPERIMENT Training phase: To reveal malicious traffic that characterizes network attacks,
we will build a machine learning model based on the LightGBM ensemble method. Due to …

… Machine Learning Analysis of SBA Before we present our machine learning protocol in Sec…
in a database to be classified by a machine learning model. The inputs to the model are the …

… with wireless technologies, Vehicular Ad Hoc Network (VANET) has … machine learning
techniques. In this paper we try to reach this goal by applying Multi-Agent Reinforcement Learning …

… In this paper, a machine learning-based RF jamming classification in wireless ad hoc networks
is proposed. we used ns-3 to simulate different jamming techniques on wireless networks…

… tools, Machine Learning. The novel architectures of Vehicular Ad-hoc Networks reduce
traffic … Machine learning algorithms help in achieving such efficiency and security. This paper …