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Science, ISSN 0036-8075, 08/2016, Volume 353, Issue 6300, pp. 691 - 694
Journal Article
Renewable and Sustainable Energy Reviews, ISSN 1364-0321, 10/2015, Volume 50, pp. 82 - 91
This paper reviews state-of-the-art on wind speed/power forecasting and solar irradiance forecasting with ensemble methods. The ensemble forecasting methods... 
Ensemble method | Wind power forecasting | Solar irradiance forecasting | Wind speed forecasting | GREEN & SUSTAINABLE SCIENCE & TECHNOLOGY | EMPIRICAL MODE DECOMPOSITION | NEURAL-NETWORKS | SPEED PREDICTION | ENERGY & FUELS | GENERATION | Analysis | Green technology | Solar energy | Electric properties
Journal Article
Artificial Intelligence Review, ISSN 0269-2821, 2/2010, Volume 33, Issue 1, pp. 1 - 39
The idea of ensemble methodology is to build a predictive model by integrating multiple models. It is well-known that ensemble methods can be used for... 
Supervised learning | Computer Science | Classification | Artificial Intelligence (incl. Robotics) | Ensemble of classifiers | Boosting | Computer Science, general | NEURAL NETWORKS | ALGORITHM | DECOMPOSITION | EXPERTS | RANDOM SUBSPACE METHOD | COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE | ACCURACY | MULTIPLE CLASSIFIERS | DECISION TREES | DIVERSITY
Journal Article
Physical Review E, ISSN 2470-0045, 09/2016, Volume 94, Issue 3
Let P-beta((V))(N-I) be the probability that a N x N beta-ensemble of random matrices with confining potential V (x) has N-I eigenvalues inside an interval I =... 
EIGENVALUE | DISTRIBUTIONS | FLUCTUATION | COMPLEX-SYSTEMS | MODELS | PHYSICS, FLUIDS & PLASMAS | ENERGY-LEVELS | SAMPLES | ATOMIC GAS | PHYSICS, MATHEMATICAL | LARGE DEVIATIONS | BOSE-EINSTEIN CONDENSATION
Journal Article
Journal Article
IEEE Transactions on Power Systems, ISSN 0885-8950, 01/2014, Volume 29, Issue 1, pp. 359 - 367
Journal Article
Proceedings of the National Academy of Sciences, ISSN 0027-8424, 09/2014, Volume 111, Issue 38, pp. E4053 - E4061
Journal Article
International Journal of Approximate Reasoning, ISSN 0888-613X, 06/2017, Volume 85, pp. 79 - 96
are granular classifiers stemming from the hybridization of Fuzzy Cognitive Maps and Rough Set Theory. Such cognitive neural networks attempt to quantify the... 
Rough set theory | Granular computing | Rough cognitive networks | Ensemble learning | Fuzzy cognitive maps | Machine learning | DESIGN | RECOGNITION | FUZZY | IMBALANCED DATA | NETWORKS | ALGORITHMS | COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE | CLASSIFIERS | PATTERN-CLASSIFICATION | TREES | MAPS | Electrical engineering | Computer science | Neural networks | Analysis
Journal Article
Physical Review E - Statistical, Nonlinear, and Soft Matter Physics, ISSN 1539-3755, 03/2009, Volume 79, Issue 3, p. 036114
In this paper we generalize the concept of random networks to describe network ensembles with nontrivial features by a statistical mechanics approach. This... 
TOPOLOGY | entropy | PHYSICS, FLUIDS & PLASMAS | probability | random processes | complex networks | MODEL | RANDOM GRAPHS | PHYSICS, MATHEMATICAL | statistical mechanics
Journal Article
Nature Neuroscience, ISSN 1097-6256, 05/2004, Volume 7, Issue 5, pp. 446 - 451
Journal Article
International Journal of Electrical Power and Energy Systems, ISSN 0142-0615, 11/2016, Volume 82, pp. 92 - 104
Journal Article
Renewable Energy, ISSN 0960-1481, 04/2016, Volume 89, pp. 671 - 679
Journal Article
Neurocomputing, ISSN 0925-2312, 2019
We investigate in this paper the architecture of deep convolutional networks. Building on existing state of the art models, we propose a reconfiguration of the... 
Deep learning | Ensemble learning | Neural net architectures | Information Retrieval |