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A review of deep learning with special emphasis on architectures, applications and recent trends
Deep learning (DL) has solved a problem that a few years ago was thought to be intractable—
the automatic recognition of patterns in spatial and temporal data with an accuracy superior …
the automatic recognition of patterns in spatial and temporal data with an accuracy superior …
Machine learning and metaheuristic methods for renewable power forecasting: a recent review
The global trend toward a green sustainable future encouraged the penetration of
renewable energies into the electricity sector to satisfy various demands of the market …
renewable energies into the electricity sector to satisfy various demands of the market …
Wind power prediction using deep neural network based meta regression and transfer learning
An innovative short term wind power prediction system is proposed which exploits the
learning ability of deep neural network based ensemble technique and the concept of …
learning ability of deep neural network based ensemble technique and the concept of …
[HTML][HTML] The application of ANFIS prediction models for thermal error compensation on CNC machine tools
Thermal errors can have significant effects on CNC machine tool accuracy. The errors come
from thermal deformations of the machine elements caused by heat sources within the …
from thermal deformations of the machine elements caused by heat sources within the …
Intelligent and robust prediction of short term wind power using genetic programming based ensemble of neural networks
The inherent instability of wind power production leads to critical problems for smooth power
generation from wind turbines, which then requires an accurate forecast of wind power. In …
generation from wind turbines, which then requires an accurate forecast of wind power. In …
RETRACTED: Artificial neural networks applications in wind energy systems: A review
R Ata - 2015 - Elsevier
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 …
explicitly that their work is original and has not been submitted to nor appeared in another …
Forecasting green roofs' potential in improving building thermal performance and mitigating urban heat island in the Mediterranean area: An artificial intelligence …
Green roofs are widely used in hot or cold climates mainly because they are capable to
improve the energy efficiency of buildings and, when implemented at a large scale, reducing …
improve the energy efficiency of buildings and, when implemented at a large scale, reducing …
Hourly forecasting of the photovoltaic electricity at any latitude using a network of artificial neural networks
Nowadays, special attention is paid to the importance of using photovoltaic (PV) systems to
tackle the problem of climate change and the energy crisis. Artificial intelligence is currently …
tackle the problem of climate change and the energy crisis. Artificial intelligence is currently …
Wind turbine power curve modeling based on Gaussian processes and artificial neural networks
An accurate estimation of the wind turbine power curve is a key issue to the provision of the
electricity that the wind farm will transfer to the grid and for a correct evaluation of the …
electricity that the wind farm will transfer to the grid and for a correct evaluation of the …
Modelling and analysis of real-world wind turbine power curves: Assessing deviations from nominal curve by neural networks
The power curve of a wind turbine describes the generated power versus instantaneous
wind speed. Assessing wind turbine performance under laboratory ideal conditions will …
wind speed. Assessing wind turbine performance under laboratory ideal conditions will …