Data

NameRiquelme Santos, José Cristóbal
DepartmentLenguajes y Sistemas Informáticos
Knowledge areaLenguajes y Sistemas Informáticos
Professional categoryCatedrático de Universidad
E-mailRequest
           

  Statistics

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  Publications

 

Article
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Temporal convolutional networks applied to energy-related time series forecasting

Lara Benítez, Pedro; Carranza García, Manuel; Luna Romera, José María; Riquelme Santos, José Cristóbal (MDPI, 2020-01-01)
Modern energy systems collect high volumes of data that can provide valuable information about energy consumption. Electric ...
Article
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A novel ensemble method for electric vehicle power consumption forecasting: Application to the Spanish system

Gómez Quiles, Catalina; Asencio Cortés, G.; Gastalver Rubio, Adolfo; Martínez-Álvarez, Francisco; Troncoso Lora, Alicia; Manresa, Joan; Riquelme Santos, José Cristóbal; Riquelme Santos, Jesús Manuel (Institute of Electrical and Electronics Engineers (IEEE), 2019-01-01)
The use of electric vehicle across the world has become one of the most challenging issues for environmental policies. The ...
Article
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Analysis of the evolution of the Spanish labour market through unsupervised learning

Luna Romera, José María; Núñez Hernández, Fernando; Martínez Ballesteros, María del Mar; Riquelme Santos, José Cristóbal; Ibáñez, Carlos Usabiaga (Institute of Electrical and Electronics Engineers (IEEE), 2019-01-01)
Unemployment in Spain is one of the biggest concerns of its inhabitants. Its unemployment rate is the second highest in ...
Article
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A Framework for Evaluating Land Use and Land Cover Classification Using Convolutional Neural Networks

Carranza García, Manuel; García Gutiérrez, Jorge; Riquelme Santos, José Cristóbal (MDPI, 2019-01-01)
Analyzing land use and land cover (LULC) using remote sensing (RS) imagery is essential for many environmental and social ...
Article
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Data Science and Big Data in Energy Forecasting

Martínez Álvarez, Francisco; Troncoso Lora, Alicia; Riquelme Santos, José Cristóbal (MDPI, 2018-11-01)
This editorial summarizes the performance of the special issue entitled Data Science and Big Data in Energy Forecasting, ...
Article
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Big Data Analytics for Discovering Electricity Consumption Patterns in Smart Cities

Pérez Chacón, Rubén; Luna Romera, José María; Troncoso Lora, Alicia; Martínez Álvarez, Francisco; Riquelme Santos, José Cristóbal (MDPI, 2018-01-01)
New technologies such as sensor networks have been incorporated into the management of buildings for organizations and ...
Article
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Recent Advances in Energy Time Series Forecasting

Martínez Álvarez, Francisco; Troncoso Lora, Alicia; Riquelme Santos, José Cristóbal (MDPI, 2017-01-01)
This editorial summarizes the performance of the special issue entitled Energy Time Series Forecasting, which was published ...
Article
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Obtaining optimal quality measures for quantitative association rules

Martínez Ballesteros, María del Mar; Troncoso Lora, Alicia; Martínez Álvarez, Francisco; Riquelme Santos, José Cristóbal (Elsevier, 2016-01-01)
There exist several works in the literature in which fitness functions based on a combination of weighted measures for the ...
Article
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An evolutionary voting for k-nearest neighbours

Mateos García, Daniel; García Gutiérrez, Jorge; Riquelme Santos, José Cristóbal (Elsevier, 2016-01-01)
This work presents an evolutionary approach to modify the voting system of the k-nearest neighbours (kNN) rule we called ...
Article
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Local models-based regression trees for very short-term wind speed prediction

Troncoso Lora, Alicia; Salcedo Sanz, S.; Casanova Mateo, C.; Riquelme Santos, José Cristóbal; Prieto, L. (Elsevier, 2015-01-01)
This paper evaluates the performance of different types of Regression Trees (RTs) in a real problem of very short-term ...
Article
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An evolutionary-weighted majority voting and support vector machines applied to contextual classification of LiDAR and imagery data fusion

García Gutiérrez, Jorge; Mateos García, Daniel; García, Mariano; Riquelme Santos, José Cristóbal (Elsevier, 2015-01-01)
Data classification is a critical step to convert remotely sensed data into thematic information. Environmental researchers have ...
Article
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A comparison of machine learning regression techniques for LiDAR-derived estimation of forest variables

García Gutiérrez, Jorge; Martínez Álvarez, Francisco; Troncoso Lora, Alicia; Riquelme Santos, José Cristóbal (Elsevier, 2015-01-01)
Light Detection and Ranging (LiDAR) is a remote sensor able to extract three-dimensional information. Environmental models ...
Article
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Improving a multi-objective evolutionary algorithm to discover quantitative association rules

Martínez Ballesteros, María del Mar; Troncoso Lora, Alicia; Martínez Álvarez, Francisco; Riquelme Santos, José Cristóbal (Springer, 2015-01-01)
This work aims at correcting flaws existing in multi-objective evolutionary schemes to discover quantitative association ...
Article
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A Survey on Data Mining Techniques Applied to Energy Time Series Forecasting

Martínez Álvarez, Francisco; Troncoso Lora, Alicia; Asencio Cortés, G.; Riquelme Santos, José Cristóbal (MDPI, 2015-01-01)
Data mining has become an essential tool during the last decade to analyze large sets of data. The variety of techniques ...
Chapter of Book
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Data Cleansing Meets Feature Selection: A Supervised Machine Learning Approach

Tallón Ballesteros, Antonio Javier; Riquelme Santos, José Cristóbal (Springer, 2015-01-01)
This paper presents a novel procedure to apply in a sequential way two data preparation techniques from a different nature ...
Article
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A multi-scale smoothing kernel for measuring time-series similarity

Troncoso Lora, Alicia; Arias, Marta; Riquelme Santos, José Cristóbal (Elsevier, 2015-01-01)
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 ...
Article
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Enhancing the scalability of a genetic algorithm to discover quantitative association rules in large-scale datasets

Martínez Ballesteros, María del Mar; Bacardit, Jaume; Troncoso Lora, Alicia; Riquelme Santos, José Cristóbal (iOS Press, 2015-01-01)
Association rule mining is a well-known methodology to discover significant and apparently hidden relations among attributes ...
Presentation
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Inferencia de Redes de Asociación de Genes Guiada por Similitud Semántica

Galván Rojas, José Luis; Nepomuceno Chamorro, Isabel de los Ángeles; Nepomuceno Chamorro, Juan Antonio; Riquelme Santos, José Cristóbal (Asociación Española para la Inteligencia Artificial, 2015-01-01)
En este trabajo se propone el uso de conocimiento a priori como heurística en métodos de inferencia de redes de genes a ...
Chapter of Book
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Data Mining Methods Applied to a Digital Forensics Task for Supervised Machine Learning

Computational Intelligence in Digital Forensics: Forensic Investigation and Applications, Vol. 555, Studies in Computational Intelligence pp 413-428 (2014); Tallón Ballesteros, Antonio Javier; Riquelme Santos, José Cristóbal (2014-01-01)
Digital forensics research includes several stages. Once we have collected the data the last goal is to obtain a model in ...
Chapter of Book
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Tackling Ant Colony Optimization Meta-Heuristic as Search Method in Feature Subset Selection Based on Correlation or Consistency Measures

Tallón Ballesteros, Antonio Javier; Riquelme Santos, José Cristóbal (Springer, 2014-01-01)
This paper introduces the use of an ant colony optimization (ACO) algorithm, called Ant System, as a search method in two ...
Presentation
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Preliminary Comparison of Techniques for Dealing with Imbalance in Software Defect Prediction

Rodríguez, Daniel; Herraiz, Israel; Harrison, Rachel; Dolado, Javier; Riquelme Santos, José Cristóbal (ACM, 2014-01-01)
Imbalanced data is a common problem in data mining when dealing with classi cation problems, where samples of a class vastly ...
Chapter of Book
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Improving the k-Nearest Neighbour Rule by an Evolutionary Voting Approach

García Gutiérrez, Jorge; Mateos García, Daniel; Riquelme Santos, José Cristóbal (Springer, 2014-01-01)
This work presents an evolutionary approach to modify the voting system of the k-Nearest Neighbours (kNN). The main novelty ...
Presentation
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Deleting or Keeping Outliers for Classifier Training?

Tallón Ballesteros, Antonio Javier; Riquelme Santos, José Cristóbal (IEEE, 2014-01-01)
This paper introduces two statistical outlier detection approaches by classes. Experiments on binary and multi-class ...
Chapter of Book
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A Comparative Study of Machine Learning Regression Methods on LiDAR Data: A Case Study

García Gutiérrez, Jorge; Martínez Álvarez, Francisco; Troncoso Lora, Alicia; Riquelme Santos, José Cristóbal (Springer, 2014-01-01)
Light Detection and Ranging (LiDAR) is a remote sensor able to extract vertical information from sensed objects. ...
Article
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Evolutionary feature selection to estimate forest stand variablesusing LiDAR

García Gutiérrez, Jorge; González Ferreiro, Eduardo; Riquelme Santos, José Cristóbal; Miranda, David; Diéguez Aranda, Ulises; Navarro Cerrillo, Rafael M. (Elsevier, 2014-01-01)
Light detection and ranging (LiDAR) has become an important tool in forestry. LiDAR-derived models are mostly developed ...
Article
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Discovering gene association networks by multi-objective evolutionary quantitative association rules

Martínez Ballesteros, María del Mar; Nepomuceno Chamorro, Isabel de los Ángeles; Riquelme Santos, José Cristóbal (Elsevier, 2014-01-01)
In the last decade, the interest in microarray technology has exponentially increased due to its ability to monitor the ...
Article
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Selecting the best measures to discover quantitative association rules

Martínez Ballesteros, María del Mar; Martínez Álvarez, Francisco; Troncoso Lora, Alicia; Riquelme Santos, José Cristóbal (Elsevier, 2014-01-01)
The majority of the existing techniques to mine association rules typically use the support and the confidence to evaluate ...
Article
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TriGen: A genetic algorithm to mine triclusters in temporal gene expression data

Gutiérrez Avilés, David; Rubio Escudero, Cristina; Martínez Álvarez, Francisco; Riquelme Santos, José Cristóbal (Elsevier, 2014-01-01)
Analyzing microarray data represents a computational challenge due to the characteristics of these data. Clustering techniques ...
Article
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A study of subgroup discovery approaches for defect prediction

Rodríguez, Daniel; Ruiz, Roberto; Riquelme Santos, José Cristóbal; Harrison, Rachel (Elsevier, 2013-01-01)
Context: Although many papers have been published on software defect prediction techniques, machine learning approaches ...
Chapter of Book
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A Kernel for Time Series Classification: Application to Atmospheric Pollutants

Arias, Marta; Troncoso Lora, Alicia; Riquelme Santos, José Cristóbal (Springer, 2013-01-01)
In this paper a kernel for time-series data is presented. The main idea of the kernel is that it is designed to recognize ...
PhD Thesis
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Nuevos modelos de Redes Neuronales Evolutivas para Clasificación Aplicación a Unidades Producto y Unidades Sigmoide

Hervás Martínez, César; Riquelme Santos, José Cristóbal; Tallón Ballesteros, Antonio Javier (2013-01-01)
Chapter of Book
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A Sensitivity Analysis for Quality Measures of Quantitative Association Rules

Martínez Ballesteros, María del Mar; Martínez Álvarez, Francisco; Troncoso Lora, Alicia; Riquelme Santos, José Cristóbal (Springer, 2013-01-01)
There exist several fitness function proposals based on a combination of weighted objectives to optimize the discovery of ...
Article
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Feature selection to enhance a two-stage evolutionary algorithm in product unit neural networks for complex classification problems

Tallón Ballesteros, Antonio Javier; Hervás Martínez, César; Riquelme Santos, José Cristóbal; Ruiz, Roberto (Elsevier, 2013-01-01)
This paper combines feature selection methods with a two-stage evolutionary classifier based on product unit neural networks. ...
PhD Thesis
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Ponderación local evolutiva de la regla kNN

Riquelme Santos, José Cristóbal; Mateos García, Daniel (2013-01-01)
En la literatura, existen numerosas técnicas para mejorar el rendimiento de la regla de los k vecinos más cercanos (en ...
PhD Thesis
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Intelligent techniques on LIDAR for environmental applications

Riquelme Santos, José Cristóbal; García Gutiérrez, Jorge (2012-06-01)
Esta propuesta de tesis está estrechamente relacionada con el campo de las técnicas inteligentes y el soft computing. A ...
Presentation
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STATService: Herramienta de análisis estadístico como soporte para la investigación con Metaheurísticas

Parejo Maestre, José Antonio; García, Jorge; Ruiz Cortés, Antonio; Riquelme Santos, José Cristóbal (2012-01-01)
Actualmente, la aplicación de técnicas estadísticas es una necesidad cuando se trabaja con metaheurísticas. A pesar de que ...
Article
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Evolutionary Generalized Radial Basis Function neural networks for improving prediction accuracy in gene classification using feature selection

Fernández Navarro, Francisco; Hervás Martínez, César; Ruiz, Roberto; Riquelme Santos, José Cristóbal (Elsevier, 2012-01-01)
Radial Basis Function Neural Networks (RBFNNs) have been successfully employed in several function approximation and pattern ...
Article
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Fast feature selection aimed at high-dimensional data via hybrid-sequential-ranked searches

Ruiz, Roberto; Riquelme Santos, José Cristóbal; García Torres, M. (Elsevier, 2012-01-01)
We address the feature subset selection problem for classification tasks. We examine the performance of two hybrid strategies ...
Article
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Searching for rules to detect defective modules: A subgroup discovery approach

Rodríguez, Daniel; Ruiz, Roberto; Riquelme Santos, José Cristóbal; Aguilar Ruiz, Jesús Salvador (Elsevier, 2012-01-01)
Data mining methods in software engineering are becoming increasingly important as they can support several aspects of the ...
Article
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EVOR-STACK: A label-dependent evolutive stacking on remote sensing data fusion

García Gutiérrez, Jorge; Mateos García, Daniel; Riquelme Santos, José Cristóbal (Elsevier, 2012-01-01)
Land use and land covers (LULC) maps are remote sensing products that are used to classify areas into different landscapes. ...
Chapter of Book
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A Non-parametric Approach for Accurate Contextual Classification of LIDAR and Imagery Data Fusion

García Gutiérrez, Jorge; Mateos García, Daniel; Riquelme Santos, José Cristóbal (Springer, 2012-01-01)
Light Detection and Ranging (LIDAR) has become a very important tool to many environmental applications. This work proposes to ...
Article
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On the evolutionary optimization of k-NN by label-dependent feature weighting

Mateos García, Daniel; García Gutiérrez, Jorge; Riquelme Santos, José Cristóbal (Elsevier, 2012-01-01)
Different approaches of feature weighting and k-value selection to improve the nearest neighbour technique can be found ...
Chapter of Book
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Analysis of Measures of Quantitative Association Rules

Martínez Ballesteros, María del Mar; Riquelme Santos, José Cristóbal (Springer, 2011-01-01)
This paper presents the analysis of relationships among different interestingness measures of quality of association rules ...
Article
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An evolutionary algorithm to discover quantitative association rules in multidimensional time series

Martínez Ballesteros, María del Mar; Martínez Álvarez, Francisco; Troncoso Lora, Alicia; Riquelme Santos, José Cristóbal (Springer, 2011-01-01)
An evolutionary approach for finding existing relationships among several variables of a multidimensional time series is ...
Article
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Energy Time Series Forecasting Based on Pattern Sequence Similarity

Martínez Álvarez, Francisco; Troncoso Lora, Alicia; Riquelme Santos, José Cristóbal; Aguilar Ruiz, Jesús Salvador (IEEE, 2011-01-01)
This paper presents a new approach to forecast the behavior of time series based on similarity of pattern sequences. ...
Presentation
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Multiobjective Simulation Optimisation in Software Project Management

Rodríguez, Daniel; Ruiz Carreira, Mercedes; Riquelme Santos, José Cristóbal; Harrison, Rachel (ACM, 2011-01-01)
Traditionally, simulation has been used by project managers in optimising decision making. However, current simulation packages ...
Chapter of Book
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A Comparative Study between Two Regression Methods on LiDAR Data: A Case Study

García Gutiérrez, Jorge; González Ferreiro, Eduardo; Mateos García, Daniel; Riquelme Santos, José Cristóbal; Miranda, David (Springer, 2011-01-01)
Airborne LiDAR (Light Detection and Ranging) has become an excellent tool for accurately assessing vegetation characteristics ...
Article
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Discovery of motifs to forecast outlier occurrence in time series

Martínez Álvarez, Francisco; Troncoso Lora, Alicia; Riquelme Santos, José Cristóbal; Aguilar Ruiz, Jesús Salvador (Elsevier, 2011-01-01)
The forecasting process of real-world time series has to deal with especially unexpected values, commonly known as outliers. ...
Chapter of Book
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Unravelling the Yeast Cell Cycle Using the TriGen Algorithm

Gutiérrez Avilés, David; Rubio Escudero, Cristina; Riquelme Santos, José Cristóbal (Springer, 2011-01-01)
Analyzing microarray data represents a computational challenge due to the characteristics of these data. Clustering ...
Article
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Automatic environmental quality assessment for mixed-land zones using lidar and intelligent techniques

García Gutiérrez, Jorge; Gonçalves Seco, Luis; Riquelme Santos, José Cristóbal (Elsevier, 2011-01-01)
Human impact on the natural environment is an evident global fact. Natural, industrial and touristic areas coexist in a ...
Chapter of Book
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Inferring Gene-Gene Associations from Quantitative Association Rules

Martínez Ballesteros, María del Mar; Nepomuceno Chamorro, Isabel de los Ángeles; Riquelme Santos, José Cristóbal (IEEE, 2011-01-01)
The microarray technique is able to monitor the change in concentration of RNA in thousands of genes simultaneously. The ...
Presentation
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On the use of algorithms to discover motifs in DNA sequences

Rubio Escudero, Cristina; Martínez Álvarez, F.; Martínez Ballesteros, María del Mar; Riquelme Santos, José Cristóbal (IEEE, 2011-01-01)
Many approaches are currently devoted to find DNA motifs in nucleotide sequences. However, this task remains challenging ...
Presentation
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Triclustering on TemporaryMicroarray Data using the TriGen Algorithm

Gutiérrez Avilés, David; Rubio Escudero, Cristina; Riquelme Santos, José Cristóbal (IEEE, 2011-01-01)
The analysis of microarray data is a computational challenge due to the characteristics of these data. Clustering techniques ...
Chapter of Book
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Computational Intelligence Techniques for Predicting Earthquakes

Martínez Álvarez, F.; Troncoso Lora, Alicia; Morales Esteban, Antonio; Riquelme Santos, José Cristóbal (Springer, 2011-01-01)
Nowadays, much effort is being devoted to develop techniques that forecast natural disasters in order to take ...
Chapter of Book
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Improving the Accuracy of a Two-Stage Algorithm in Evolutionary Product Unit Neural Networks for Classification by Means of Feature Selection

Tallón Ballesteros, Antonio Javier; Hervás Martínez, César; Riquelme Santos, José Cristóbal; Ruiz, Roberto (Springer, 2011-01-01)
This paper introduces a methodology that improves the accuracy of a two-stage algorithm in evolutionary product unit neural ...
Chapter of Book
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Revisiting the Yeast Cell Cycle Problem with the Improved TriGen Algorithm

Gutiérrez Avilés, David; Rubio Escudero, Cristina; Riquelme Santos, José Cristóbal (IEEE, 2011-01-01)
Analyzing microarray data represents a computational challenge due to the characteristics of these data. Clustering ...
PhD Thesis
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Evolutionary Algorithms to Discover Quantitative Association Rules

Riquelme Santos, José Cristóbal; Troncoso Lora, Alicia; Martínez Ballesteros, María del Mar (2011-01-01)
Article
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Inferring gene regression networks with model trees

Nepomuceno Chamorro, Isabel de los Ángeles; Aguilar Ruiz, Jesús Salvador; Riquelme Santos, José Cristóbal (BioMed Central, 2010-01-01)
Background: Novel strategies are required in order to handle the huge amount of data produced by microarray technologies. ...
Article
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Inferring gene regression networks with model trees

Aguilar Ruiz, Jesús Salvador; Riquelme Santos, José Cristóbal; Nepomuceno Chamorro, Isabel de los Ángeles (2010-01-01)
Background: Novel strategies are required in order to handle the huge amount of data produced by microarray technologies. ...
Chapter of Book
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A SVM and k-NN Restricted Stacking to Improve Land Use and Land Cover Classification

García Gutiérrez, Jorge; Mateos García, Daniel; Riquelme Santos, José Cristóbal (2010-01-01)
Land use and land cover (LULC) maps are remote sensing products that are used to classify areas into different landscapes. ...
Chapter of Book
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Using Remote Data Mining on LIDAR and Imagery Fusion Data to Develop Land Cover Maps

García Gutiérrez, Jorge; Martínez Álvarez, Francisco; Riquelme Santos, José Cristóbal (2010-01-01)
Remote sensing based on imagery has traditionally been the main tool used to extract land uses and land cover (LULC) maps. ...
Chapter of Book
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Evolutionary q-Gaussian Radial Basis Functions for Improving Prediction Accuracy of Gene Classification Using Feature Selection

Fernández Navarro, Francisco; Hervás Martínez, César; Gutiérrez, Pedro Antonio; Ruiz Sánchez, Roberto; Riquelme Santos, José Cristóbal (2010-01-01)
This paper proposes a Radial Basis Function Neural Network (RBFNN) which reproduces different Radial Basis Functions (RBFs) ...
Chapter of Book
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Label Dependent Evolutionary Feature Weighting for Remote Sensing Data

Mateos García, Daniel; García Gutiérrez, Jorge; Riquelme Santos, José Cristóbal (2010-01-01)
Nearest neighbour (NN) is a very common classifier used to develop important remote sensing products like land use and ...
Chapter of Book
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Improving Time Series Forecasting by Discovering Frequent Episodes in Sequences

Martínez Álvarez, Francisco; Troncoso Lora, Alicia; Riquelme Santos, José Cristóbal (2009-01-01)
This work aims to improve an existing time series forecasting algorithm –LBF– by the application of frequent episodes ...
Chapter of Book
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Quantitative Association Rules Applied to Climatological Time Series Forecasting

Martínez Ballesteros, María del Mar; Martínez Álvarez, Francisco; Troncoso Lora, Alicia; Riquelme Santos, José Cristóbal (2009-01-01)
This work presents the discovering of association rules based on evolutionary techniques in order to obtain relationships ...
Article
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Evolutionary techniques applied to the optimal short-term scheduling of the electrical energy production

Troncoso Lora, Alicia; Riquelme Santos, José Cristóbal; Aguilar Ruiz, Jesús Salvador; Riquelme Santos, Jesús Manuel (Elsevier, 2008-01-01)
This paper presents an evolutionary technique applied to the optimal short-term scheduling (24 h) of the electric ...
Chapter of Book
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LBF: A Labeled-Based Forecasting Algorithm and Its Application to Electricity Price Time Series

Martínez Álvarez, Francisco; Troncoso Lora, Alicia; Riquelme Santos, José Cristóbal; Aguilar Ruiz, Jesús Salvador (2008-01-01)
A new approach is presented in this work with the aim of predicting time series behaviors. A previous labeling of the ...
Chapter of Book
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Partitioning-Clustering Techniques Applied to the Electricity Price Time Series

Martínez Álvarez, Francisco; Troncoso Lora, Alicia; Riquelme Santos, José Cristóbal; Riquelme Santos, Jesús Manuel (2007-01-01)
Clustering is used to generate groupings of data from a large dataset, with the intention of representing the behavior of ...
Chapter of Book
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Detection of Microcalcifications in Mammographies Based on Linear Pixel Prediction and Support-Vector Machines

Martínez Álvarez, Francisco; Troncoso Lora, Alicia; Riquelme Santos, José Cristóbal; Aguilar Ruiz, Jesús Salvador (2007-01-01)
Breast cancer is one of the diseases causing the largest number of deaths among women. Its early detection has been proved ...
Article
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Natural Encoding for Evolutionary Supervised Learning

Aguilar Ruiz, Jesús Salvador; Giráldez Rojo, Raúl; Riquelme Santos, José Cristóbal (IEEE, 2007-01-01)
Some of the most influential factors in the quality of the solutions found by an evolutionary algorithm (EA) are a ...
Article
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Electricity Market Price Forecasting Based on Weighted Nearest Neighbors Techniques

Troncoso Lora, Alicia; Riquelme Santos, Jesús Manuel; Gómez Expósito, Antonio; Martínez Ramos, José Luis; Riquelme Santos, José Cristóbal (Institute of Electrical and Electronics Engineers (IEEE), 2007-01-01)
This paper presents a simple technique to forecast next-day electricity market prices based on the weighted nearest neighbors ...
Chapter of Book
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Data streams classification by incremental rule learning with parameterized generalization

Ferrer Troyano, Francisco Javier; Aguilar Ruiz, Jesús Salvador; Riquelme Santos, José Cristóbal (2006-01-01)
Mining data streams is a challenging task that requires online systems based on incremental learning approaches. This paper ...
Article
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Minería de Datos: Conceptos y Tendencias

Riquelme Santos, José Cristóbal; Ruiz, Roberto; Gilbert, Karina (IBERAMIA : Sociedad Iberoamericana de Inteligencia Artificial, 2006-01-01)
Hoy en día, la minería de datos (MD) está consiguiendo cada vez más captar la atención de las empresas. Todavía es infrecuente ...
PhD Thesis
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Heurísticas de selección de atributos para datos de gran dimensionalidad

Riquelme Santos, José Cristóbal; Aguilar Ruiz, Jesús Salvador; Ruiz Sánchez, Roberto (2006-01-01)
Esta tesis doctoral se enmarca en el campo del aprendizaje automático y aborda uno de sus principales problemas, como es ...
Article
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Incremental wrapper-based gene selection from microarray data for cancer classification

Ruiz, Roberto; Riquelme Santos, José Cristóbal; Aguilar Ruiz, Jesús Salvador (Elsevier, 2006-01-01)
Gene expression microarray is a rapidly maturing technology that provides the opportunity to assay the expression levels ...
Chapter of Book
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Analysis of Feature Rankings for Classification

Ruiz Sánchez, Roberto; Aguilar Ruiz, Jesús Salvador; Riquelme Santos, José Cristóbal; Díaz Díaz, Norberto (2005-01-01)
Different ways of contrast generated rankings by feature selection algorithms are presented in this paper, showing several ...
Chapter of Book
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Incremental rule learning based on example nearness from numerical data streams

Ferrer Troyano, Francisco Javier; Aguilar Ruiz, Jesús Salvador; Riquelme Santos, José Cristóbal (2005-01-01)
Mining data streams is a challenging task that requires online systems based on incremental learning approaches. This paper ...
Chapter of Book
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Heuristic Search over a Ranking for Feature Selection

Ruiz Sánchez, Roberto; Riquelme Santos, José Cristóbal; Aguilar Ruiz, Jesús Salvador (2005-01-01)
In this work, we suggest a new feature selection technique that lets us use the wrapper approach for finding a well suited ...
Article
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Knowledge-Based Fast Evaluation for Evolutionary Learning

Giráldez Rojo, Raúl; Aguilar Ruiz, Jesús Salvador; Riquelme Santos, José Cristóbal (IEEE, 2005-01-01)
The increasing amount of information available is encouraging the search for efficient techniques to improve the data ...
Article
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Connecting Segments for Visual Data Exploration and Interactive Mining of Decision Rules

Ferrer Troyano, Francisco Javier; Aguilar Ruiz, Jesús Salvador; Riquelme Santos, José Cristóbal (Graz University of Technology, Institut für Informationssysteme und Computer Medien, 2005-01-01)
Visualization has become an essential support throughout the KDD process in order to extract hidden information from huge ...
Article
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Incremental Rule Learning and Border Examples Selection from Numerical Data Streams

Ferrer Troyano, Francisco Javier; Aguilar Ruiz, Jesús Salvador; Riquelme Santos, José Cristóbal (Graz University of Technology, Institut für Informationssysteme und Computer Medie, 2005-01-01)
Mining data streams is a challenging task that requires online systems based on incremental learning approaches. This paper ...
Presentation
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A Tool to Obtain a Hierarchical Qualitative Rules from Quantitative Data

Aguilar, Jesús; Riquelme Santos, José Cristóbal; Toro Bonilla, Miguel (Springer, 2005-01-01)
A tool to obtain a classifier system from labelled databases is presented. The result is a hierarchical set of rules to ...
PhD Thesis
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Técnicas avanzadas de predicción y optimización aplicadas a sistemas de potencia

Riquelme Santos, José Cristóbal; Martínez Ramos, José Luis; Troncoso Lora, Alicia (2004-07-01)
Esta tesis está enmarcada básicamente dentro de dos campos de investigación, la minería de datos y la optimización. ...
Chapter of Book
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Evolutionary segmentation of yeast genome

Mateos García, Daniel; Riquelme Santos, José Cristóbal; Aguilar Ruiz, Jesús Salvador (2004-01-01)
Segmentation algorithms differ from clustering algorithms with regard to how to deal with the physical location of genes ...
Chapter of Book
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Statistical Test-Based Evolutionary Segmentation of Yeast Genome

Aguilar Ruiz, Jesús Salvador; Mateos García, Daniel; Giráldez Rojo, Raúl; Riquelme Santos, José Cristóbal (2004-01-01)
Segmentation algorithms emerge observing fluctuations of DNA sequences in alternative homogeneous domains, which are named ...
Chapter of Book
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Wrapper for Ranking Feature Selection

Ruiz Sánchez, Roberto; Aguilar Ruiz, Jesús Salvador; Riquelme Santos, José Cristóbal (2004-01-01)
We propose a new feature selection criterion not based on calculated measures between attributes, or complex and costly ...
Chapter of Book
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Discovering decision rules from numerical data streams

Ferrer Troyano, Francisco Javier; Aguilar Ruiz, Jesús Salvador; Riquelme Santos, José Cristóbal (2004-01-01)
This paper presents a scalable learning algorithm to classify numerical, low dimensionality, high-cardinality, time-changing ...
Chapter of Book
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Multidimensional Data Visual Exploration by Interactive Information Segments

Ferrer Troyano, Francisco Javier; Aguilar Ruiz, Jesús Salvador; Riquelme Santos, José Cristóbal (2004-01-01)
Visualization techniques provide an outstanding role in KDD process for data analysis and mining. However, one image does ...
Chapter of Book
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Data Mining Approaches to Diffuse Large B–Cell Lymphoma Gene Expression Data Interpretation

Aguilar Ruiz, Jesús Salvador; Azuaje, Francisco; Riquelme Santos, José Cristóbal (2004-01-01)
This paper presents a comprehensive study of gene expression patterns originating from a diffuse large B–cell lymphoma ...
PhD Thesis
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Mejoras en eficiencia y eficacia de algoritmos evolutivos para aprendizaje supervisado

Riquelme Santos, José Cristóbal; Aguilar Ruiz, Jesús Salvador; Giráldez Rojo, Raúl (2004-01-01)
Los algoritmos evolutivos conforman una de las más importantes familias de modelos computacionales con aplicación en el ...
PhD Thesis
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Avances en la toma de decisiones en proyectos de desarrollo de software

Ramos Román, Isabel; Riquelme Santos, José Cristóbal; Aroba Páez, Javier (2003-11-01)
Chapter of Book
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An efficient data structure for decision rules discovery

Giráldez Rojo, Raúl; Aguilar Ruiz, Jesús Salvador; Riquelme Santos, José Cristóbal (2003-01-01)
The increasing amount of information available is encouraging the search for efficient techniques to improve the data ...
Chapter of Book
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Influence of kNN-Based Load Forecasting Errors on Optimal Energy Production

Troncoso Lora, Alicia; Riquelme Santos, José Cristóbal; Martínez Ramos, José Luis; Riquelme Santos, Jesús Manuel; Gómez Expósito, Antonio (2003-01-01)
This paper presents a study of the influence of the accuracy of hourly load forecasting on the energy planning and operation ...
Chapter of Book
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Natural Coding: A More Efficient Representation for Evolutionary Learning

Giráldez Rojo, Raúl; Aguilar Ruiz, Jesús Salvador; Riquelme Santos, José Cristóbal (2003-01-01)
To select an adequate coding is one of the main problems in applications based on Evolutionary Algorithms. Many codings ...
Chapter of Book
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Mining Low Dimensionality Data Streams of Continuous Attributes

Ferrer Troyano, Francisco Javier; Aguilar Ruiz, Jesús Salvador; Riquelme Santos, José Cristóbal (2003-01-01)
This paper presents an incremental and scalable learning algorithm in order to mine numeric, low dimensionality, ...
Chapter of Book
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Prototype-based mining of numeric data streams

Ferrer Troyano, Francisco Javier; Aguilar Ruiz, Jesús Salvador; Riquelme Santos, José Cristóbal (2003-01-01)
Great organizations collect open-ended and time-changing data received at a high speed. The possibility of extracting ...
Chapter of Book
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Application of Evolutionary Computation Techniques to the Optimal Short-Term Scheduling of the Electrical Energy Production

Troncoso Lora, Alicia; Riquelme Santos, José Cristóbal; Martínez Ramos, José Luis; Riquelme Santos, Jesús Manuel; Gómez Expósito, Antonio (2003-01-01)
In this paper, an evolutionary technique applied to the optimal short-term scheduling (24 hours) of the electric energy ...
Chapter of Book
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Time-Series Prediction: Application to the Short-Term Electric Energy Demand

Troncoso Lora, Alicia; Riquelme Santos, Jesús Manuel; Riquelme Santos, José Cristóbal; Gómez Expósito, Antonio; Martínez Ramos, José Luis (2003-01-01)
This paper describes a time-series prediction method based on the kNN technique. The proposed methodology is applied to ...
Chapter of Book
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Clustering Main Concepts from e-Mails

Aguilar Ruiz, Jesús Salvador; Rodríguez Baena, Domingo S.; Cohen, Paul R.; Riquelme Santos, José Cristóbal (2003-01-01)
E–mail is one of the most common ways to communicate, assuming, in some cases, up to 75% of a company’s communication, in ...
Chapter of Book
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NLC: A Measure Based on Projections

Ruiz Sánchez, Roberto; Riquelme Santos, José Cristóbal; Aguilar Ruiz, Jesús Salvador (2003-01-01)
In this paper, we propose a new feature selection criterion. It is based on the projections of data set elements onto each ...
Chapter of Book
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Visualization techniques of management rules for software development projects

Mata Vázquez, Jacinto; Alvarez Macías, José Luis; Riquelme Santos, José Cristóbal; Ramos Román, Isabel; Aguilar Ruiz, Jesús Salvador; Ferrer Troyano, Francisco Javier (2003-01-01)
The application of data mining techniques to the managing of software development projects (SDP) is not an uncommon ...
Chapter of Book
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Fast Feature Selection by Means of Projections

Ruiz Sánchez, Roberto; Riquelme Santos, José Cristóbal; Aguilar Ruiz, Jesús Salvador (2003-01-01)
The attribute selection techniques for supervised learning, used in the preprocessing phase to emphasize the most relevant ...
Chapter of Book
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Fast Feature Ranking Algorithm

Ruiz Sánchez, Roberto; Riquelme Santos, José Cristóbal; Aguilar Ruiz, Jesús Salvador (2003-01-01)
The attribute selection techniques for supervised learning, used in the preprocessing phase to emphasize the most relevant ...
Chapter of Book
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Empirical Evaluation of the Difficulty of Finding a Good Value of k for the Nearest Neighbor

Ferrer Troyano, Francisco Javier; Aguilar Ruiz, Jesús Salvador; Riquelme Santos, José Cristóbal (2003-01-01)
As an analysis of the classification accuracy bound for the Nearest Neighbor technique, in this work we have studied if ...
Article
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Supervised learning by means of accuracy-aware evolutionary algorithms

Riquelme Santos, José Cristóbal; Aguilar Ruiz, Jesús Salvador; Valle Sevillano, Carmelo del (Elsevier, 2003-01-01)
This paper describes a new approach, HIerarchical DEcision Rules (HIDER), for learning generalizable rules in continuous ...
Article
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Finding representative patterns withordered projections

Riquelme Santos, José Cristóbal; Aguilar Ruiz, Jesús Salvador; Toro Bonilla, Miguel (Elsevier, 2003-01-01)
This paper presents a new approach to 2nding representative patterns for dataset editing. The algorithm patterns by ...
Article
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Evolutionary Learning of Hierarchical Decision Rules

Aguilar Ruiz, Jesús Salvador; Riquelme Santos, José Cristóbal; Toro Bonilla, Miguel (IEEE, 2003-01-01)
This paper describes an approach based on evolutionary algorithms, hierarchical decision rules (HIDER), for learning rules ...
Chapter of Book
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A Comparison of Two Techniques for Next- Day Electricity Price Forecasting

Troncoso Lora, Alicia; Riquelme Santos, Jesús Manuel; Riquelme Santos, José Cristóbal; Gómez Expósito, Antonio; Martínez Ramos, José Luis (2002-01-01)
In the framework of competitive markets, the market’s participants need energy price forecasts in order to determine their ...
Chapter of Book
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Mining interesting regions using an evolutionary algorithm

Alvarez Macías, José Luis; Mata Vázquez, Jacinto; Riquelme Santos, José Cristóbal (2002-01-01)
In this paper, we offer a new method to induce interesting knowledge from the relevant sets of data in databases for ...
Chapter of Book
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Electricity Market Price Forecasting: Neural Networks versus Weighted-Distance k Nearest Neighbours

Troncoso Lora, Alicia; Riquelme Santos, José Cristóbal; Riquelme Santos, Jesús Manuel; Martínez Ramos, José Luis; Gómez Expósito, Antonio (2002-01-01)
In today’s deregulated markets, forecasting energy prices is becoming more and more important. In the short term, expected ...
Chapter of Book
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An evolutionary algorithm to discover numeric association rules

Mata Vázquez, Jacinto; Alvarez Macías, José Luis; Riquelme Santos, José Cristóbal (2002-01-01)
Association rules are one of the most used tools to discover relationships among attributes in a database. Nowadays, there ...
Chapter of Book
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SOAP: Efficient Feature Selection of Numeric Attributes

Ruiz Sánchez, Roberto; Aguilar Ruiz, Jesús Salvador; Riquelme Santos, José Cristóbal (2002-01-01)
The attribute selection techniques for supervised learning, used in the preprocessing phase to emphasize the most relevant ...
Presentation
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Generation of Management Rules through System Dynamics and Evolutionary Computation

Aguilar Ruiz, Jesús Salvador; Riquelme Santos, José Cristóbal; Rodríguez, Daniel; Ramos Román, Isabel (Springer, 2002-01-01)
Decision making has been traditionally based on a managers experience. This paper, however, discusses how a software ...
Presentation
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Improving the Evolutionary Coding for Machine Learning Tasks

Aguilar Ruiz, Jesús Salvador; Riquelme Santos, José Cristóbal; Valle Sevillano, Carmelo del (IOS Press, 2002-01-01)
The most influential factors in the quality of the solutions found by an evolutionary algorithm are a correct coding of ...
Chapter of Book
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Non-parametric Nearest Neighbor with Local Adaptation

Ferrer Troyano, Francisco Javier; Aguilar Ruiz, Jesús Salvador; Riquelme Santos, José Cristóbal (2001-01-01)
The k-Nearest Neighbor algorithm (k-NN) uses a classification criterion that depends on the parameter k. Usually, the value ...
Chapter of Book
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Separation Surfaces through Genetic Programming

Riquelme Santos, José Cristóbal; Giráldez Rojo, Raúl; Aguilar Ruiz, Jesús Salvador; Ruiz Sánchez, Roberto (2001-01-01)
The aim of this paper is to describe a study for the obtaining, symbolically, of the separation surfaces between clusters ...
Chapter of Book
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OBLIC: Classification System Using Evolutionary Algorithm

Alvarez Macías, José Luis; Mata Vázquez, Jacinto; Riquelme Santos, José Cristóbal (2001-01-01)
We present a new classification system based on Evolutionary Algorithm (EA), OBLIC. This tool is an OBLIque Classification ...
Article
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An evolutionary approach to estimating software development projects

Aguilar Ruiz, Jesús Salvador; Ramos Román, Isabel; Riquelme Santos, José Cristóbal; Toro Bonilla, Miguel (Elsevier, 2001-01-01)
The use of dynamic models and simulation environments in connection with software projects paved the way for tools that ...
Article
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An Evolutionary and Local Search Algorithm for Motion Planning of Two Manipulators

Ridao Carlini, Miguel Ángel; Camacho, Eduardo F.; Riquelme Santos, José Cristóbal; Toro Bonilla, Miguel (Wiley, 2001-01-01)
A method for obtaining coordinated motion plans of robot manipulators is presented. A decoupled planning approach has been ...
Article
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Data Set Editing by Ordered Projection

Aguilar, Jesús S.; Riquelme Santos, José Cristóbal; Toro Bonilla, Miguel (IOS Press, 2001-01-01)
This paper presents a new approach to data set editing. The algorithm (EOP: Editing by Ordered Projection) has some ...
Presentation
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SEGESOFT: un entorno de entrenamiento para la gestión de proyectos software

Riquelme Santos, José Cristóbal; Ramos Román, Isabel; Aguilar, Jesús; Ferrer Troyano, Francisco Javier; Toro Bonilla, Miguel; Dolado, J.; Ruiz de Infante, A.; Tuya, J.; Fernández, P.; Prieto, M.A.; Ruiz Carreira, Mercedes; Rodríguez García, D.; Satpathy, M.; Harrison, R.; Matilla, R.; Álvarez, M.A. (SISTEDES: Ingeniería de Software y las Tecnologías de Desarrollo de Software, 2001-01-01)
La gestión de proyectos se puede considerar todavía como un arte en el cual el uso de la información cuantitativa tiende ...
Article
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Discovering hierarchical decision rules with evolutive algorithms in supervised learning

Riquelme Santos, José Cristóbal; Aguilar, Jesús S.; Toro Bonilla, Miguel (2000-01-01)
This paper describes a new approach, HIDER (HIerarchical DEcision Rules), for learning rules in continuous and discrete ...
Presentation
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CGO y COBLI: clasificadores oblícuos basados en algoritmos genéticos

Mora Pérez, José; Alvarez Macías, José Luis; Riquelme Santos, José Cristóbal; Mata Vázquez, Jacinto (1999-01-01)
Chapter of Book
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Overload screening of transmission systems using neural networks

Riquelme Santos, José Cristóbal; Gómez Expósito, Antonio; Martínez Ramos, José Luis; Peças Lopes, J.A. (1998-01-01)
The process of determining whether a power system is in a secure or insecure state is a crucial task which must be addressed ...
Chapter of Book
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Decision Queue Classifier for Supervised Learning Using Rotated Hyperboxes

Aguilar Ruiz, Jesús Salvador; Riquelme Santos, José Cristóbal; Toro Bonilla, Miguel (1998-01-01)
This article describes a new system for learning rules using rotated hyperboxes as individuals of a genetic algorithm (GA). ...
Article
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Una herramienta basada en algoritmos genéticos para obtener un clasificador jerárquico en aprendizaje supervisado

Riquelme Santos, José Cristóbal; Aguilar, Jesús; Toro Bonilla, Miguel (Asociación Española para la Inteligencia Artificial, 1998-01-01)
Presentation
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Using Genetic Algorithms with Variable-length Individuals for Planning Two-Manipulators Motion

Riquelme Santos, José Cristóbal; Ridao Carlini, Miguel Ángel; Camacho, Eduardo F.; Toro Bonilla, Miguel (Springer Nature, 1998-01-01)
A method based on genetic algorithms for obtaining coordinated motion plans of manipulator robots is presented. A decoupled ...
PhD Thesis