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Mostrando ítems 1-10 de 22
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
Enhancing the scalability of a genetic algorithm to discover quantitative association rules in large-scale datasets
(iOS Press, 2015)
Association rule mining is a well-known methodology to discover significant and apparently hidden relations among attributes in a subspace of instances from datasets. Genetic algorithms have been extensively used to find ...
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
Pattern recognition to forecast seismic time series
(Elsevier, 2010)
Earthquakes arrive without previous warning and can destroy a whole city in a few seconds, causing numerous deaths and economical losses. Nowadays, a great effort is being made to develop techniques that forecast these ...
Artículo
Scatter search-based identification of local patterns with positive and negative correlations in gene expression data
(Elsevier, 2015)
This paper presents a scatter search approach based on linear correlations among genes to find biclusters, which include both shifting and scaling patterns and negatively correlated patterns contrarily to most ...
Artículo
A multi-scale smoothing kernel for measuring time-series similarity
(Elsevier, 2015)
In this paper a kernel for time-series data is introduced so that it can be used for any data mining task that relies on a similarity or distance metric. The main idea of our kernel is that it should recognize as highly ...
Artículo
Integrating biological knowledge based on functional annotations for biclustering of gene expression data
(Elsevier, 2015)
Gene expression data analysis is based on the assumption that co-expressed genes imply co-regulated genes. This assumption is being reformulated because the co-expression of a group of genes may be the result of an ...