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Listar por autor "Martínez Álvarez, Francisco"
Mostrando ítems 41-55 de 55
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Ponencia
Mining Quantitative Association Rules in Microarray Data Using Evolutive Algorithms
Martínez Ballesteros, María del Mar; Rubio Escudero, Cristina; Riquelme Santos, José Cristóbal; Martínez Álvarez, Francisco (SciTePress, 2011)The microarray technique is able to monitor the change in concentration of RNA in thousands of genes simultaneously. The ...
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Artículo
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)There exist several works in the literature in which fitness functions based on a combination of weighted measures for the ...
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Ponencia
On the performance of deep learning models for time series classification in streaming
Lara Benítez, Pedro; Carranza García, Manuel; Martínez Álvarez, Francisco; Riquelme Santos, José Cristóbal (Springer, 2020)Processing data streams arriving at high speed requires the development of models that can provide fast and accurate ...
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Ponencia
On the use of algorithms to discover motifs in DNA sequences
Rubio Escudero, Cristina; Martínez Álvarez, Francisco; Martínez Ballesteros, María del Mar; Riquelme Santos, José Cristóbal (IEEE, 2011)Many approaches are currently devoted to find DNA motifs in nucleotide sequences. However, this task remains challenging ...
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Capítulo de Libro
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)Clustering is used to generate groupings of data from a large dataset, with the intention of representing the behavior of ...
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Artículo
PHILNet: A novel efficient approach for time series forecasting using deep learning
Jiménez Navarro, Manuel Jesús; Martínez Ballesteros, María del Mar; Martínez Álvarez, Francisco; Asencio Cortés, Gualberto (ScienceDirect, 2023)Time series is one of the most common data types in the industry nowadays. Forecasting the future of a time series behavior ...
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Capítulo de Libro
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)This work presents the discovering of association rules based on evolutionary techniques in order to obtain relationships ...
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Ponencia
Random Hyper-parameter Search-Based Deep Neural Network for Power Consumption Forecasting
Torres, J. F.; Gutiérrez Avilés, David; Troncoso Lora, Alicia; Martínez Álvarez, Francisco (Springer, 2019)In this paper, we introduce a deep learning approach, based on feed-forward neural networks, for big data time series ...
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Ponencia
Real-Time Big Data Analytics in Smart Cities from LoRa-Based IoT Networks
Fernández, Antonio M.; Gutiérrez Avilés, David; Troncoso Lora, Alicia; Martínez Álvarez, Francisco (Springer, 2019)The currently burst of the Internet of Things (IoT) tech-nologies implies the emergence of new lines of investigation ...
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Artículo
Recent Advances in Energy Time Series Forecasting
Martínez Álvarez, Francisco; Troncoso Lora, Alicia; Riquelme Santos, José Cristóbal (MDPI, 2017)This editorial summarizes the performance of the special issue entitled Energy Time Series Forecasting, which was published ...
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Artículo
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)The majority of the existing techniques to mine association rules typically use the support and the confidence to evaluate ...
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Ponencia
SmartFD: A Real Big Data Application for Electrical Fraud Detection
Gutiérrez Avilés, David; Fábregas, J. A.; Tejedor, Javier; Martínez Álvarez, Francisco; Troncoso Lora, Alicia; Arcos Vargas, Ángel; Riquelme Santos, José Cristóbal (Springer, 2018)The main objective of this paper is the application of big data analytics to a real case in the field of smart electric ...
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Tesis Doctoral
Statistical analysis of different seismogenic zonings of the Iberian Peninsula and adjacent areas through a Geographic Information System
Amaro Mellado, José Lázaro (2019-09-23)The knowledge of the seismic hazard in the Iberian Peninsula (IP) and its neighboring area is important to address the ...
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Artículo
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)Analyzing microarray data represents a computational challenge due to the characteristics of these data. Clustering techniques ...
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Capítulo de Libro
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)Remote sensing based on imagery has traditionally been the main tool used to extract land uses and land cover (LULC) maps. ...