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Changes in temperature extremes for 21st century scenarios over South America derived from a multi-model ensemble of regional climate models
(Inter-Research, 2016-05)
This study examines a set of 4 temperature extreme indices (cold and warm nighttime and daytime indices) from an ensemble of 4 regional climate models (RCMs) for present and future periods in South America (SA). These ...
Notions of the ergodic hierarchy for curved statistical manifolds
(Elsevier Science, 2017-10)
We present an extension of the ergodic, mixing, and Bernoulli levels of the ergodic hierarchy for statistical models on curved manifolds, making use of elements of the information geometry. This extension focuses on the ...
A differential evolution algorithm to optimise the combination of classifier and cluster ensembles
(Inderscience EnterprisesGeneva, 2015)
Unsupervised models can provide supplementary soft constraints to help classify new
data since similar instances are more likely to share the same class label. In this context, this paper reports on a study on how to make ...
Stock closing price forecasting using ensembles of constructive neural networks
(2014-01-01)
Efficient automatic systems which continuously learn over long periods of time, and manage to evolve its knowledge, by discarding obsolete parts of it and acquiring new ones to reflect recent data, are difficult to be ...
Multi-objective clustering ensemble for gene expression data analysis
(ELSEVIER SCIENCE BV, 2009)
In this paper, we present an algorithm for cluster analysis that integrates aspects from cluster ensemble and multi-objective clustering. The algorithm is based on a Pareto-based multi-objective genetic algorithm, with a ...
Fractal Neural Network: A new ensemble of fractal geometry and convolutional neural networks for the classification of histology images
(2021-03-15)
Classification of histology images is a task that has been widely explored on recent computer vision researches. The most studied approach for this task has been the application of deep learning through a convolutional ...
Estimating parameters with ensemble-based data assimilation : a review.
(Meteorological Soc Jpn, 2013-01)
Weather forecast and earth system models usually have a number of parameters, which are often optimizedmanually by trial and error. Several studies have proposed objective methods to estimate model parameters using ...
A fuzzy distance-based ensemble of deep models for cervical cancer detection
(2022-06-01)
Background and Objective: Cervical cancer is one of the leading causes of women's death. Like any other disease, cervical cancer's early detection and treatment with the best possible medical advice are the paramount steps ...
Assimilation of ozone measurements in the air quality model AURORA by using the Ensemble Kalman Filter
(2011 50th IEEE Conference on Decision and Control and European Control Conference, 2020)