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Artículo
Energy Time Series Forecasting Based on Pattern Sequence Similarity
(IEEE, 2011)
This paper presents a new approach to forecast the behavior of time series based on similarity of pattern sequences. First, clustering techniques are used with the aim of grouping and labeling the samples from a data set. ...
Artículo
Machine learning techniques to discover genes with potential prognosis role in Alzheimer’s disease using different biological sources
(Elsevier, 2017)
Alzheimer’s disease is a complex progressive neurodegenerative brain disorder, being its prevalence ex pected to rise over the next decades. Unconventional strategies for elucidating the genetic mechanisms are necessary ...
Artículo
Discovering gene association networks by multi-objective evolutionary quantitative association rules
(Elsevier, 2014)
In the last decade, the interest in microarray technology has exponentially increased due to its ability to monitor the expression of thousands of genes simultaneously. The reconstruction of gene association networks ...
Artículo
An evolutionary algorithm to discover quantitative association rules in multidimensional time series
(Springer, 2011)
An evolutionary approach for finding existing relationships among several variables of a multidimensional time series is presented in this work. The proposed model to discover these relationships is based on quantitative ...
Artículo
Merging subsets of attributes to improve a hybrid consistency-based filter: a case of study in product unit neural networks
(Taylor and Francis, 2016)
This paper presents a quality enhancement of the selected features by a hybrid filter-based jointly on feature ranking and feature subset selection (FR-FSS) using a consistency-based measure via merging new features which ...
Artículo
Evolutionary Generalized Radial Basis Function neural networks for improving prediction accuracy in gene classification using feature selection
(Elsevier, 2012)
Radial Basis Function Neural Networks (RBFNNs) have been successfully employed in several function approximation and pattern recognition problems. The use of different RBFs in RBFNN has been reported in the literature ...
Artículo
Discovery of motifs to forecast outlier occurrence in time series
(Elsevier, 2011)
The forecasting process of real-world time series has to deal with especially unexpected values, commonly known as outliers. Outliers in time series can lead to unreliable modeling and poor forecasts. Therefore, the ...
Artículo
Mining quantitative association rules based on evolutionary computation and its application to atmospheric pollution
(IOS Press, 2010)
This research presents the mining of quantitative association rules based on evolutionary computation techniques. First, a real-coded genetic algorithm that extends the well-known binary-coded CHC algorithm has been ...