[HTML][HTML] Paradigm shift for predictive maintenance and condition monitoring from Industry 4.0 to Industry 5.0: A systematic review, challenges and case study
This paper examines the integration of Industry 5.0 principles with advanced predictive
maintenance (PdM) and condition monitoring (CM) practices, based on Industry 4.0's …
maintenance (PdM) and condition monitoring (CM) practices, based on Industry 4.0's …
[HTML][HTML] A comprehensive survey on load forecasting hybrid models: Navigating the Futuristic demand response patterns through experts and intelligent systems
Load forecasting is a crucial task, which is carried out by utility companies for sake of power
grids' successful planning, optimized operation and control, enhanced performance, and …
grids' successful planning, optimized operation and control, enhanced performance, and …
[HTML][HTML] Energy consumption prediction in water treatment plants using deep learning with data augmentation
Wastewater treatment plants (WWTPs) are energy-intensive facilities that play a critical role
in meeting stringent effluent quality regulations. Accurate prediction of energy consumption …
in meeting stringent effluent quality regulations. Accurate prediction of energy consumption …
[HTML][HTML] Enhancing wind power prediction with self-attentive variational autoencoders: A comparative study
Accurate wind power prediction is critical for efficient grid management and the integration of
renewable energy sources into the power grid. This study presents an effective deep …
renewable energy sources into the power grid. This study presents an effective deep …
Cloud intrusion detection framework using variational auto encoder Wasserstein generative adversarial network optimized with archerfish hunting optimization …
The cloud computing environment has been severely harmed by security issues, which has
a negative impact on the healthy and sustainable development of the cloud. Intrusion …
a negative impact on the healthy and sustainable development of the cloud. Intrusion …
A novel ultra-short-term wind power prediction method based on XA mechanism
A major difficulty in integrating large scale wind power generation in an electrical power
system is that wind generated power appears to be erratic, intermittent, and volatile. In this …
system is that wind generated power appears to be erratic, intermittent, and volatile. In this …
A flexible and lightweight deep learning weather forecasting model
G Zenkner, S Navarro-Martinez - Applied Intelligence, 2023 - Springer
Numerical weather prediction is an established weather forecasting technique in which
equations describing wind, temperature, pressure and humidity are solved using the current …
equations describing wind, temperature, pressure and humidity are solved using the current …
Attack detection using artificial intelligence methods for SCADA security
Technological developments and transformations have rapidly risen since the Fourth
Industrial Revolution. The prevalence of industrial devices interconnected over the wireless …
Industrial Revolution. The prevalence of industrial devices interconnected over the wireless …
Wind power forecasting method of large-scale wind turbine clusters based on DBSCAN clustering and an enhanced hunter-prey optimization algorithm
G Hou, J Wang, Y Fan - Energy Conversion and Management, 2024 - Elsevier
As the large-scale grid connection of wind turbines poses challenges to the safe and stable
operation of the power grid, it is necessary to forecast the power of wind turbine clusters …
operation of the power grid, it is necessary to forecast the power of wind turbine clusters …
[HTML][HTML] Estimating the mean cutting force of conical picks using random forest with salp swarm algorithm
Conical picks are widely used as cutting tools in shearers and roadheaders, and the mean
cutting force (MCF) is one of the important parameters affecting conical pick performance. As …
cutting force (MCF) is one of the important parameters affecting conical pick performance. As …