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Mining Quantitative Association Rules in Microarray Data Using Evolutive Algorithms
(SciTePress, 2011)
The microarray technique is able to monitor the change in concentration of RNA in thousands of genes simultaneously. The interest in this technique has grown exponentially in recent years and the difficulties in analyzing ...
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
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 ...
Capítulo de Libro
A Sensitivity Analysis for Quality Measures of Quantitative Association Rules
(Springer, 2013)
There exist several fitness function proposals based on a combination of weighted objectives to optimize the discovery of association rules. Nevertheless, some differences in the measures used to assess the quality of ...
Capítulo de Libro
Using Remote Data Mining on LIDAR and Imagery Fusion Data to Develop Land Cover Maps
(2010)
Remote sensing based on imagery has traditionally been the main tool used to extract land uses and land cover (LULC) maps. However, more powerful tools are needed in order to fulfill organizations requirements. Thus, this ...
Artículo
Improving a multi-objective evolutionary algorithm to discover quantitative association rules
(Springer, 2015)
This work aims at correcting flaws existing in multi-objective evolutionary schemes to discover quantitative association rules, specifically those based on the wellknown non-dominated sorting genetic algorithm-II (NSGA-II). ...