Anomaly detection is an important method for monitoring network traffic where is important to
successfully distinguish normal traffic from abnormal traffic. For this purpose, one could use …

Abstract The Intrusion Detection System plays a significant role in discovering malicious
activities and provides better network security solutions than other conventional defense …

This study optimizes biomass chemical looping processes (BCLpro), a technique for
converting biomass to energy, through machine learning (ML) for sustainable energy …

With the rapid growth of digital technology communications are overwhelmed by network
data traffic. The demand for the internet is growing every day in today's cyber world, raising …

Cyber security has been drawing massive attention in recent years due to human reliance
on new technology, and systems. Therefore, securing these systems against cyber-attacks …

One of the key challenges of the machine learning (ML) based intrusion detection system
(IDS) is the expensive computation time which is largely caused by the redundant …

Cardiovascular disease (CVD) is a leading cause of death globally. The unpredictability and
severity of CVDs, such as sudden cardiac arrests, necessitate real-time monitoring and …

The traditional site environmental investigation and pollution identification mainly relies on
manual filling of paper forms and experience-weighted scoring, which have limitations in …

In the realm of manufacturing processes, equipment failures can result in substantial
financial losses and pose significant safety hazards. Consequently, prior research has …

Modernizing power systems into smart grids has introduced numerous benefits, including
enhanced efficiency, reliability, and integration of renewable energy sources. However, this …