Perfil del autor: Martínez Ballesteros, María del Mar
Datos institucionales
Nombre | Martínez Ballesteros, María del Mar |
Departamento | Lenguajes y Sistemas Informáticos |
Área de conocimiento | Lenguajes y Sistemas Informáticos |
Categoría profesional | Profesora Titular de Universidad |
Correo electrónico | Solicitar |
Estadísticas
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Nº publicaciones
55
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Nº visitas
5556
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Nº descargas
9439
Publicaciones |
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Capítulo de Libro
Uso de herramientas software colaborativas para el seguimiento, estudio y evaluación de clases de enseñanzas prácticas y desarrollo
(Dykinson, 2024)
Para ayudar a la integración de todos los desarrollos individuales existen herramientas de control de versiones como ... |
Artículo
Explaining deep learning models for ozone pollution prediction via embedded feature selection
(ScienceDirect, 2024)
Ambient air pollution is a pervasive global issue that poses significant health risks. Among pollutants, ozone (O3) is ... |
Ponencia
Embedded Temporal Feature Selection for Time Series Forecasting Using Deep Learning
(Springer Link, 2023)
Traditional time series forecasting models often use all available variables, including potentially irrelevant or noisy ... |
Ponencia
Deep Learning-Based Approach for Sleep Apnea Detection Using Physiological Signals
(Springer Link, 2023)
This paper explores the use of deep learning techniques for detecting sleep apnea. Sleep apnea is a common sleep disorder ... |
Ponencia
Association Rule Analysis of Student Satisfaction Surveys for Teaching Quality Evaluation
(Springer Link, 2023)
The quality of university teaching is essential for the success of students and the academic excellence of an educational ... |
Ponencia
A New Hybrid CNN-LSTM for Wind Power Forecasting in Ethiopia
(Springer Link, 2023)
Renewable energies are currently experiencing promising growth as an alternative solution to minimize the emission of ... |
Ponencia
A Feature Selection and Association Rule Approach to Identify Genes Associated with Metastasis and Low Survival in Sarcoma
(SpringerLink, 2023)
Sarcomas are rare mesodermal tumors of heterogeneous nature and have a higher incidence in children. The relative 5-year ... |
Ponencia
Explaining Learned Patterns in Deep Learning by Association Rules Mining
(SpringerLink, 2023)
This paper proposes a novel approach that combines an association rule algorithm with a deep learning model to enhance the ... |
Ponencia
Evolutionary computation to explain deep learning models for time series forecasting
(Association for Computing Machinery, 2023)
Deep learning has become one of the most useful tools in the last years to mine information from large datasets. Despite ... |
Ponencia
A bioinspired ensemble approach for multi-horizon reference evapotranspiration forecasting in Portugal
(Association for Computing Machinery, 2023)
The year 2022 was the driest year in Portugal since 1931 with 97% of territory in severe drought. Water is especially ... |
Tesis Doctoral
Novel efficient deep learning architectures for time series forecasting
(2023)
This thesis focuses on the study of time series prediction using the technique known as deep learning or neural networks. ... |
Artículo
A Bayesian Optimization-Based LSTM Model for Wind Power Forecasting in the Adama District, Ethiopia
(MDPI, 2023)
Renewable energies, such as solar and wind power, have become promising sources of energy to address the increase in ... |
Artículo |
Artículo
A new approach based on association rules to add explainability to time series forecasting models
(ScienceDirect, 2023)
Machine learning and deep learning have become the most useful and powerful tools in the last years to mine information ... |
Artículo
PHILNet: A novel efficient approach for time series forecasting using deep learning
(ScienceDirect, 2023)
Time series is one of the most common data types in the industry nowadays. Forecasting the future of a time series behavior ... |
Trabajo Fin de Grado
Curvas de Edwards para firma digital: EdDSA
(2023)
EdDSA is the digital signature used in the Signal protocol. The development of this protocol was a milestone for instant ... |
Artículo
A new deep learning architecture with inductive bias balance for transformer oil temperature forecasting
(Springer Nature, 2023)
Ensuring the optimal performance of power transformers is a laborious task in which the insulation system plays a vital ... |
Ponencia
A novel approach to discover numerical association based on the Coronavirus Optimization Algorithm
(Association for Computing Machinery, 2022)
The disease caused by the SARS-CoV-2 (COVID-19) has affected millions of people around the world since its detection in ... |
Ponencia
Feature-Aware Drop Layer (FADL): A Nonparametric Neural Network Layer for Feature Selection
(SpringerLink, 2022)
Neural networks have proven to be a good alternative in application fields such as healthcare, time-series forecasting and ... |
Artículo
Explainable machine learning for sleep apnea prediction
(ScienceDirect, 2022)
Machine and deep learning has become one of the most useful tools in the last years as a diagnosis-decision-support tool ... |
Artículo
Autoencoded DNA methylation data to predict breast cancer recurrence: Machine learning models and gene-weight significance
(Elsevier, 2020)
Breast cancer is the most frequent cancer in women and the second most frequent overall after lung cancer. Although the ... |
Tesis Doctoral
New internal and external validation indices for clustering in Big Data
(2019)
Esta tesis, presentada como un compendio de artículos de investigación, analiza el concepto de índices de validación de ... |
Artículo
External clustering validity index based on chi-squared statistical test
(Elsevier, 2019)
Clustering is one of the most commonly used techniques in data mining. Its main goal is to group objects into clusters so ... |
Artículo
Analysis of the evolution of the Spanish labour market through unsupervised learning
(Institute of Electrical and Electronics Engineers (IEEE), 2019)
Unemployment in Spain is one of the biggest concerns of its inhabitants. Its unemployment rate is the second highest in ... |
Artículo
MRQAR: A generic MapReduce framework to discover quantitative association rules in big data problems
(Elsevier, 2018)
Many algorithms have emerged to address the discovery of quantitative association rules from datasets in the last years. ... |
Artículo
An approach to validity indices for clustering techniques in Big Data
(Springer, 2018)
Clustering analysis is one of the most used Machine Learning techniques to discover groups among data objects. Some ... |
Ponencia
Aproximación al índice externo de validación de clustering basado en chi cuadrado
(Asociación Española para la Inteligencia Artificial (AEPIA), 2018)
El clustering es una de las técnicas más utilizadas en minería de datos. Tiene como objetivo principal agrupar datos en ... |
Artículo
Applications of Computational Intelligence in Time Series
(Hindawi, 2017)
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Artículo
Machine learning techniques to discover genes with potential prognosis role in Alzheimer’s disease using different biological sources
(Elsevier, 2017)
Alzheimer’s disease is a complex progressive neurodegenerative brain disorder, being its prevalence ex pected to rise over ... |
Ponencia
Predicción de módulos defectuosos como un problema de optimización multiobjetivo
(Asociación de Ingeniería del Software y Tecnologías de Desarrollo de Software (SISTEDES), 2017)
La dificultad de aplicar técnicas de análisis de datos al problema de la calidad del software radica principalmente en dos ... |
Artículo
A study of the suitability of autoencoders for preprocessing data in breast cancer experimentation
(Elsevier, 2017)
Breast cancer is the most common cause of cancer death in women. Today, post-transcriptional protein products of the genes ... |
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 ... |
Ponencia
A Nearest Neighbours-Based Algorithm for Big Time Series Data Forecasting
(Springer, 2016)
A forecasting algorithm for big data time series is presented in this work. A nearest neighbours-based strategy is adopted ... |
Ponencia
An Approach to Silhouette and Dunn Clustering Indices Applied to Big Data in Spark
(Springer, 2016)
K-Means and Bisecting K-Means clustering algorithms need the optimal number into which the dataset may be divided. Spark ... |
Ponencia
Discovery of Genes Implied in Cancer by Genetic Algorithms and Association Rules
(Springer, 2016)
This work proposes a methodology to identify genes highly related with cancer. In particular, a multi-objective evolutionary ... |
Ponencia
MOPNAR-BigData: un diseño MapReduce para la extracción de reglas de asociación cuantitativas en problemas de big data
(Asociación Española de Inteligencia Artificial, 2015)
El término big data se ha extendido rápidamente en el área de la minera de datos debido a que las grandes cantidades de ... |
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 ... |
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 ... |
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 ... |
Artículo
Discovering gene association networks by multi-objective evolutionary quantitative association rules
(Elsevier, 2014)
In the last decade, the interest in microarray technology has exponentially increased due to its ability to monitor the ... |
Artículo
Discovering quantitative association rules: A novel approach based on evolutionary algorithms
(IOS Press, 2014)
This work proposes a novel methodology to improve the discovery of quantitative association rules in continuous datasets. ... |
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 ... |
Ponencia
On the use of algorithms to discover motifs in DNA sequences
(IEEE, 2011)
Many approaches are currently devoted to find DNA motifs in nucleotide sequences. However, this task remains challenging ... |
Artículo
Extensiones para el Ciclo de Mejora Continua en la enseñanza e investigación de Ingeniería Informática
(2011)
Este trabajo expone cómo añadiendo aspectos relacionados con la vigilancia tecnológica, las técnicas creativas aplicadas ... |
Artículo
Evolutionary association rules for total ozone content modeling from satellite observations
(Elsevier, 2011)
In this paper we propose an evolutionary method of association rules discovery (EQAR, Evolutionary Quan titative Association ... |
Capítulo de Libro
Inferring Gene-Gene Associations from Quantitative Association Rules
(IEEE, 2011)
The microarray technique is able to monitor the change in concentration of RNA in thousands of genes simultaneously. The ... |
Ponencia
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 ... |
Capítulo de Libro
Analysis of Measures of Quantitative Association Rules
(Springer, 2011)
This paper presents the analysis of relationships among different interestingness measures of quality of association rules ... |
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 ... |
Tesis Doctoral |
Ponencia
EVFUZZYSYSTEM: evolución de sistemas difusos para problemas de regresión multi-dimensionales
(Universidad de Huelva, 2010)
Este trabajo presenta EvFuzzySystem, un método evolutivo que permite el diseño com pleto de sistemas de lógica difusa, ... |
Ponencia
Cis-cop: Multiobjective identification of cis-regulatory modules based on constrains
(Universidad de Huelva, 2010)
Gene expression regulation is an intricate, dynamic phenomenon essential for all biolog ical functions. The necessary ... |
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, ... |
Capítulo de Libro
Quantitative Association Rules Applied to Climatological Time Series Forecasting
(2009)
This work presents the discovering of association rules based on evolutionary techniques in order to obtain relationships ... |
Ponencia
Descubriendo Reglas de Asociación Numéricas entre Series Temporales
(Universidad de Sevilla, 2009)
Este trabajo presenta el descubrimiento de reglas de asociación basadas en técnicas evolutivas para obtener relaciones ... |