Para ayudar a la integración de todos los desarrollos individuales existen herramientas de control de versiones como ...

Ambient air pollution is a pervasive global issue that poses significant health risks. Among pollutants, ozone (O3) is ...

Traditional time series forecasting models often use all available variables, including potentially irrelevant or noisy ...

This paper explores the use of deep learning techniques for detecting sleep apnea. Sleep apnea is a common sleep disorder ...

The quality of university teaching is essential for the success of students and the academic excellence of an educational ...

Renewable energies are currently experiencing promising growth as an alternative solution to minimize the emission of ...

Sarcomas are rare mesodermal tumors of heterogeneous nature and have a higher incidence in children. The relative 5-year ...

This paper proposes a novel approach that combines an association rule algorithm with a deep learning model to enhance the ...

Deep learning has become one of the most useful tools in the last years to mine information from large datasets. Despite ...

The year 2022 was the driest year in Portugal since 1931 with 97% of territory in severe drought. Water is especially ...

This thesis focuses on the study of time series prediction using the technique known as deep learning or neural networks. ...

Renewable energies, such as solar and wind power, have become promising sources of energy to address the increase in ...

Machine learning and deep learning have become the most useful and powerful tools in the last years to mine information ...

Time series is one of the most common data types in the industry nowadays. Forecasting the future of a time series behavior ...

EdDSA is the digital signature used in the Signal protocol. The development of this protocol was a milestone for instant ...

The disease caused by the SARS-CoV-2 (COVID-19) has affected millions of people around the world since its detection in ...

Neural networks have proven to be a good alternative in application fields such as healthcare, time-series forecasting and ...

Machine and deep learning has become one of the most useful tools in the last years as a diagnosis-decision-support tool ...

Breast cancer is the most frequent cancer in women and the second most frequent overall after lung cancer. Although the ...

Esta tesis, presentada como un compendio de artículos de investigación, analiza el concepto de índices de validación de ...

Clustering is one of the most commonly used techniques in data mining. Its main goal is to group objects into clusters so ...

Unemployment in Spain is one of the biggest concerns of its inhabitants. Its unemployment rate is the second highest in ...

Many algorithms have emerged to address the discovery of quantitative association rules from datasets in the last years. ...

Clustering analysis is one of the most used Machine Learning techniques to discover groups among data objects. Some ...

El clustering es una de las técnicas más utilizadas en minería de datos. Tiene como objetivo principal agrupar datos en ...

Breast cancer is the most common cause of cancer death in women. Today, post-transcriptional protein products of the genes ...

Alzheimer’s disease is a complex progressive neurodegenerative brain disorder, being its prevalence ex pected to rise over ...

La dificultad de aplicar técnicas de análisis de datos al problema de la calidad del software radica principalmente en dos ...

There exist several works in the literature in which fitness functions based on a combination of weighted measures for the ...

This work proposes a methodology to identify genes highly related with cancer. In particular, a multi-objective evolutionary ...

A forecasting algorithm for big data time series is presented in this work. A nearest neighbours-based strategy is adopted ...

K-Means and Bisecting K-Means clustering algorithms need the optimal number into which the dataset may be divided. Spark ...

El término big data se ha extendido rápidamente en el área de la minera de datos debido a que las grandes cantidades de ...

Association rule mining is a well-known methodology to discover significant and apparently hidden relations among attributes ...

This work aims at correcting flaws existing in multi-objective evolutionary schemes to discover quantitative association ...

The majority of the existing techniques to mine association rules typically use the support and the confidence to evaluate ...

In the last decade, the interest in microarray technology has exponentially increased due to its ability to monitor the ...

There exist several fitness function proposals based on a combination of weighted objectives to optimize the discovery of ...

Many approaches are currently devoted to find DNA motifs in nucleotide sequences. However, this task remains challenging ...

Este trabajo expone cómo añadiendo aspectos relacionados con la vigilancia tecnológica, las técnicas creativas aplicadas ...

In this paper we propose an evolutionary method of association rules discovery (EQAR, Evolutionary Quan titative Association ...

The microarray technique is able to monitor the change in concentration of RNA in thousands of genes simultaneously. The ...

The microarray technique is able to monitor the change in concentration of RNA in thousands of genes simultaneously. The ...

This paper presents the analysis of relationships among different interestingness measures of quality of association rules ...

An evolutionary approach for finding existing relationships among several variables of a multidimensional time series is ...

Este trabajo presenta EvFuzzySystem, un método evolutivo que permite el diseño com pleto de sistemas de lógica difusa, ...

Gene expression regulation is an intricate, dynamic phenomenon essential for all biolog ical functions. The necessary ...

This research presents the mining of quantitative association rules based on evolutionary computation techniques. First, ...

This work presents the discovering of association rules based on evolutionary techniques in order to obtain relationships ...

Este trabajo presenta el descubrimiento de reglas de asociación basadas en técnicas evolutivas para obtener relaciones ...