Production of electricity from the burning of fossil fuels has caused an increase in the
emission of greenhouse gases. In the long run, greenhouse gases cause harm to the …

In this paper, multiple featured machine learning algorithms and deep learning algorithms
are applied in forecasting the electric vehicles charging load profile from real datasets of …

Accurate prediction of electric power generation in combined cycle power plants is
challenging yet crucial, especially when employing machine learning techniques like …

Forecasting of daily loads is crucial for the Distribution System Operators (DSO).
Contemporary short-term load forecasting models (STLF) are very well recognized and …

Accurate instantaneous electricity peak load prediction is crucial for efficient capacity
planning and cost-effective electricity network establishment. This paper aims to enhance …

This study uses the Scopus and Web of Science databases to review quantitative methods
to forecast electricity consumption from 2015 to 2024. Using the PRISMA approach, 175 …

This study has focused on describing the pH response of the CIP (clean in place) rinsing
process in order to assess the volume of water consumed and rinsing time. A pilot plant with …

The rapid growth of Indonesia's population increases electricity consumption. Unfortunately,
this growth is not followed by the development of new electrical energy sources. Therefore …

Among contemporary computational techniques, Artificial Neural Network (ANN) and
Adaptive Neuro-Fuzzy Inference System (ANFIS) are favoured because of their capacity to …

In this paper, a hybrid fuzzy-based method is suggested for determining India's best system
for power generation. This suggested approach was created using a fuzzy-based …