Class imbalance (CI) in classification problems arises when the number of observations
belonging to one class is lower than the other. Ensemble learning combines multiple models …

Software Defined Networking (SDN) has emerged as a promising and exciting option for the
future growth of the internet. SDN has increased the flexibility and transparency of the …

Machine learning (ML) provides effective solutions to develop efficient intrusion detection
system (IDS) for various environments. In the present paper, a diversified study of various …

Internet of Things (IoT) is the fastest growing technology that has applications in various
domains such as healthcare, transportation. It interconnects trillions of smart devices through …

The hydrogen production rate of TiO2 photocatalytic water splitting is significantly influenced
by various doped elements and experimental conditions (ie, dopant/Ti mole ratio, calcination …

The kind of cyber threat prevalent and most dangerous to networked systems is the
Distributed Denial of Service (DDoS), especially with expanded connection of Internet of …

The state of charge (SOC) prediction for an electric vehicle battery pack is critical to ensure
the reliability, efficiency, and life of the battery pack. Various techniques and statistical …

An intelligent malware prediction system is needed for monitoring the network traffic of
traditional and future network attacks. The Internet of Things (IoT) is fully connected and …

Identifying network anomaly detection is important since they may carry critical information in
circumstances such as a burst of intrusions, privacy theft, system damage and fraudulent …

This study presents an advanced methodology tailored for enhancing the performance of
Intrusion Detection Systems (IDS) deployed in Internet of Things (IoT) networks within smart …