Bayesian network (BN) modeling is a rapidly advancing field. Here we explore new methods
by which BN model development and application are being joined with other tools and …

The use of renewable energy resources, especially wind power, is receiving strong attention
from governments and private institutions, since it is considered one of the best and most …

Layout optimization is one of the methods to increase wind farm's utilization rate and power
output. Previous researches have revealed that different hub height wind turbines may …

Wind energy farms are moving into deeper and more remote waters to benefit from
availability of more space for the installation of wind turbines as well as higher wind speed …

Classification problems and their corresponding solving approaches constitute one of the
fields of machine learning. The application of classification schemes in Renewable Energy …

Abstract So-called Measure-Correlate-Predict (MCP) methods have been extensively
proposed in renewable energy related literature to estimate the wind resources that …

For the last years, the research and development in the field of Renewable Energy has been
growing due to the need of Renewable Energy as an extended and reliable source of …

Wind speed knowledge is prerequisite in the siting of wind turbines. In consequence the
wind energy use requires meticulous and specified knowledge of the wind characteristics at …

This paper evaluates the performance of different types of Regression Trees (RTs) in a real
problem of very short-term wind speed prediction from measuring data in wind farms. RT is a …

To effectively meet the ambitious objectives set by the Paris Agreement, gaining a deeper
understanding of the relationships between the key technologies involved in mitigation …