Applied Machine Learning Techniques for Performance Analysis in Large Wind Farms

Machine Learning techniques for applied Information Extraction

Performance analysis of modeling framework for wind speed prediction in wind farms

This paper focuses on the analysis of prediction of wind speed in the wind farms. The performance of modeling can be analyzed by using the real time data with different heights of the wind mill. Artificial Neural Network is used here to develop models for predicting wind speed in wind farms. The models are mainly based on back propagation neural network and radial basis function neural network....

Machine Learning Techniques for Face Analysis

In recent years there has been a growing interest in improving all aspects of the interaction between humans and computers with the clear goal of achieving a natural interaction, similar to the way human–human interaction takes place. The most expressive way humans display emotions is through facial expressions. Humans detect and interpret faces and facial expressions in a scene with little or ...

Symbolic dynamics applied to velocity time-series in wind farms

Symbolic dynamics applied to velocity time-series in wind farms K. Karamanos, I.S. Mistakidis, S.I. Mistakidis and I.E. Sarris4,∗ 1 Complex Systems Group, Institute of Nuclear and Particle Physics, NCSR Demokritos, GR-15310, Aghia Paraskevi, Attiki, Greece. 2 Department of Physical Sciences and Applications, Hellenic Army Academy, Vari, Attiki, Greece. 3 Zentrum für Optische Quantentechnologien...

Advanced machine learning methods for wind erosion monitoring in southern Iran

Extended abstract Introduction Wind erosion is one the most important factors of land degradation in the arid and semi-arid areas and it is one the most serious environmental problems in the world. In Fars province, 17 cities are prone to wind erosion and are considered as critical zones of wind erosion. One of the most important factors in soil wind erosion is land use/cover change. T...