This study presents a broad view of the current state of the art of ML applications in the
manufacturing sectors that have a considerable impact on sustainability and the …

One of the conditions of submission of a paper for publication is that authors declare
explicitly that their work is original and has not been submitted to nor appeared in another …

Forecasting wind speed is a crucial issue in the wind power industry, and wind energy is
gradually coming to be viewed as one of the most promising alternative energy sources …

Wind speed (WS) prediction has become popular nowadays due to increasing demand for
wind power generation and competitive development in wind energy. Many prediction …

Over the past decade, renewable energy resources, such as wind, solar, biomass, ocean
energy and other kinds of energy, are becoming attractive technologies for building green …

This paper compares three types of neural networks trained using particle swarm
optimization (PSO) for use in the short term prediction of wind speed. The three types of …

Wind power generated by wind has non-schedule nature due to stochastic nature of
meteorological variable. Hence energy business and control of wind power generation …

This study introduces a novel hybrid forecasting model for wind power generation. It
integrates Artificial Neural Networks, data clustering, and Particle Swarm Optimization …

Accurate and stable wind speed forecasting is of critical importance in the wind power
industry and has measurable influence on power-system management and the stability of …

A number of wind speed forecasting techniques are available in order to predict the
uncertainty of the wind, which is key to estimate wind power generation availability for the …