Alex Aligbe

TL;DR: An Artificial Neural Network model was trained, validated and tested with five consumer input attributes which comprises type of apartment, number of occupants, average daily power supply, scored categories of electrical appliances and scored behavioural energy usage pattern to determine the estimated monthly payment for electricity consumed by residential consumers.

TL;DR: The method proposed in this work can provide a basis for the design of a variable capacitor to keep the generated voltage of wind-driven SERG within desired limits despite wind speed and load variation.

TL;DR: There is an increase in operational cost due to increased energy loss in the windings as a result of voltage variations from the balanced state, with balanced over voltage operation showing more cost severity among the voltage variations considered.

TL;DR: Daily jet fuel test records for jet-A1 fuel provide an opportunity for developing a predictive model that can be used for jet fuel properties prediction on a given day, based on previous data trends and analysis using data pattern recognition, as an indication of the variation of jetfuel properties with daily weather variation.

TL;DR: A detailed review of the existing wireless power transfer technologies, principles of operation, applications and the opportunities for future research in this area of emerging technology is given in this paper, where the authors also discuss the potential of WPT in the Internet of Things (IoT) and other future technologies.