… machine-learning techniques to wireless ad hoc routing. In particular, this dissertation shows
that machine learning … router congestion in wireless ad hoc networks to improve distributed …

… the IEEE 802.11p wireless technology 176 to enable communications with vehicles on the
177 road [3]. The RSU also provides the access point 178 (AP) in wireless Ad Hoc networks [3]…

… ad hoc networks (VANETs) are among the most investigated topics in the field of mobile ad
hoc networks (… algorithm for different ad-hoc network architectures, such as wireless sensor …

… ad hoc routing as a cooperative reinforcement learning problem. In this paper, agents are
used to optimize the performance of a network on … An ad hoc network is a collection of wireless …

… On this basis, we explore the application of machine learning in wireless ad hoc network
and build a deep reinforcement learning model of wireless ad hoc network based on the …

… This paper presents a machine learning (ML) algorithm for recognition and low-cost tracking
… readings in ad-hoc wireless sensor fields. The randomly distributed wireless sensors are …

… Among modern machine learning frameworks used for deep learning, TensorFlow … machine
learning [16]. The authors used the open-source NSL-KDD dataset to perform deep learning …

… wireless environments. We propose a reinforcement learning-based CRAHN network
configuration method that (re)configures a cluster-based ad-hoc network by sharing the …

… in mobile Ad hoc networks." Materials Today: Proceedings (2021). [21] TJ Nagalakshmi,
AK … , “ Machine learning models to detect the black hole attack in wireless ad hoc network.” …

… Wireless sensor networks represent a special class of ad hoc networks [2]. They are made
up of many smart sensor nodes of small sizes, limited power, at low-cost, and multi-functional (…