Unsupervised machine learning for networking: Techniques, applications and research challenges
While machine learning and artificial intelligence have long been applied in networking
research, the bulk of such works has focused on supervised learning. Recently, there has …
research, the bulk of such works has focused on supervised learning. Recently, there has …
Routing in wireless sensor networks using machine learning techniques: Challenges and opportunities
Energy conservation is the primary task in Wireless Sensor Networks (WSNs) as these tiny
sensor nodes are the backbone of today's Internet of Things (IoT) applications. These nodes …
sensor nodes are the backbone of today's Internet of Things (IoT) applications. These nodes …
Machine learning techniques for energy efficiency and anomaly detection in hybrid wireless sensor networks
Wireless sensor networks (WSNs) are among the most popular wireless technologies for
sensor communication purposes nowadays. Usually, WSNs are developed for specific …
sensor communication purposes nowadays. Usually, WSNs are developed for specific …
[HTML][HTML] A comprehensive approach for the clustering of similar-performance cells for the design of a lithium-ion battery module for electric vehicles
An energy-storage system comprised of lithium-ion battery modules is considered to be a
core component of new energy vehicles, as it provides the main power source for the …
core component of new energy vehicles, as it provides the main power source for the …
An efficient quality of services based wireless sensor network for anomaly detection using soft computing approaches
Wireless sensor network (WSN) is widely acceptable communication network where human-
intervention is less. Another prominent factors are cheap in cost and covers huge area of …
intervention is less. Another prominent factors are cheap in cost and covers huge area of …
Neural networks in wireless networks: Techniques, applications and guidelines
The design of modern wireless networks, which involves decision making and parameter
optimization, is quite challenging due to the highly dynamic, and often unknown …
optimization, is quite challenging due to the highly dynamic, and often unknown …
A neuro-fuzzy approach for intrusion detection in energy efficient sensor routing
WirelessSensor Network systems (WSNs) have received noteworthy research consideration
because of their elite qualities like broad capacity to detect the physical world phenomenon …
because of their elite qualities like broad capacity to detect the physical world phenomenon …
Energy efficient clustering and routing in a wireless sensor networks
GR Asha - Procedia computer science, 2018 - Elsevier
Abstract Wireless Sensor Network (WSN) is instrumental in transferring the data gathered by
Sensors mounted on the Sensors Nodes (SNs) to the Base Station (BS). Lifetime of WSN is …
Sensors mounted on the Sensors Nodes (SNs) to the Base Station (BS). Lifetime of WSN is …
[PDF][PDF] Neural network based energy efficiency in wireless sensor networks: A survey
The main concern in Wireless Sensor Networks is how to handle with their limited energy
resources. The performance of Wireless Sensor Networks strongly depends on their lifetime …
resources. The performance of Wireless Sensor Networks strongly depends on their lifetime …
Lithium-ion battery packs formation with improved electrochemical performance for electric vehicles: experimental and clustering analysis
With the increase of production of electrical vehicles (EVs) and battery packs, lithium ion
batteries inconsistency problem has drawn much attention. Lithium ion battery imbalance …
batteries inconsistency problem has drawn much attention. Lithium ion battery imbalance …