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Mostrando ítems 1-10 de 15
Artículo
Selecting the best measures to discover quantitative association rules
(Elsevier, 2014)
The majority of the existing techniques to mine association rules typically use the support and the confidence to evaluate the quality of the rules obtained. However, these two measures may not be sufficient to properly ...
Artículo
Obtaining optimal quality measures for quantitative association rules
(Elsevier, 2016)
There exist several works in the literature in which fitness functions based on a combination of weighted measures for the discovery of association rules have been proposed. Nevertheless, some differences in the measures ...
Artículo
Big Data Analytics for Discovering Electricity Consumption Patterns in Smart Cities
(MDPI, 2018)
New technologies such as sensor networks have been incorporated into the management of buildings for organizations and cities. Sensor networks have led to an exponential increase in the volume of data available in recent ...
Artículo
Applications of Computational Intelligence in Time Series
(Hindawi, 2017)
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
A Novel Method for Seismogenic Zoning Based on Triclustering: Application to the Iberian Peninsula
(MDPI, 2015)
A previous definition of seismogenic zones is required to do a probabilistic seismic hazard analysis for areas of spread and low seismic activity. Traditional zoning methods are based on the available seismic catalog and ...
Artículo
Data Science and Big Data in Energy Forecasting
(MDPI, 2018-11)
This editorial summarizes the performance of the special issue entitled Data Science and Big Data in Energy Forecasting, which was published at MDPI’s Energies journal. The special issue took place in 2017 and accepted a ...
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
A Survey on Data Mining Techniques Applied to Energy Time Series Forecasting
(MDPI, 2015)
Data mining has become an essential tool during the last decade to analyze large sets of data. The variety of techniques it includes and the successful results obtained in many application fields, make this family of ...
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 ...