Disruption prediction and mitigation is of key importance in the development of sustainable tokamak reactors.Machine learning has become a key tool in this endeavour.In this paper, multiple machine learning models are tested and compared.A focus has been placed on the analysis of a transition to dimensionless input quantities.The methods used Omega
Relevance of the work is caused by the need to develop new highly effective systems pointing solar batteries to the Sun.Objective: development of two-coordinate guidance system of solar panels to the sun for photovoltaic power plants to provide the desired pointing accuracy and energy consumption minimization using a guidance system valve engines.R
Insulator defect detection Wok Brushes using autonomous aerial vehicles (AAVs) images is a promising method for power transmission line inspections.However, varying sizes, orientations, and complex backgrounds of insulator defects result in high false negatives and low accuracy.Previous studies have not adequately incorporated self-attention mechan