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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
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
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 ...