This paper presents a review of the central theories involved in hybrid models based on
fuzzy systems and artificial neural networks, mainly focused on supervised methods for …

Energy planning models (EPMs) play an indispensable role in policy formulation and energy
sector development. The forecasting of energy demand and supply is at the heart of an EPM …

Energy is vital for sustainable development of any nation–be it social, economic or
environment. In the past decade energy consumption has increased exponentially globally …

Interest in using artificial neural networks (ANNs) for forecasting has led to a tremendous
surge in research activities in the past decade. While ANNs provide a great deal of promise …

Load forecasting has become one of the major areas of research in electrical engineering,
and most traditional forecasting models and artificial intelligence techniques have been tried …

The present study reviews the publications that examine the application of machine learning
(ML) approaches in occupational accident analysis. The review process includes four …

This paper presents a new time series modeling for short term load forecasting, which can
model the valuable experiences of the expert operators. This approach can accurately …

Load forecasting has been a conventional and important process in electric utilities since the
early 20 th century. Due to the deregulation of the electric utility industry, the utilities tend to …

Short-term load forecasting is mainly utilized in control centers to explore the changing
patterns of consumer loads and predict the load value at a certain time in the future. It is one …

Load frequency control or automatic generation control is one of the main operations that
take place daily when considering a modern power system or not. The objectives of load …