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Listar por autor "Martínez Álvarez, Francisco"
Mostrando ítems 21-40 de 55
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Artículo
Deformation forecasting of a hydropower dam by hybridizing a long short-term memory deep learning network with the coronavirus optimization algorithm
Bui, Kien-Trinh T.; Torres, José F.; Gutiérrez Avilés, David; Nhu, Viet-Ha; Bui, Dieu Tien; Martínez Álvarez, Francisco (Wiley, 2022)The safety operation and management of hydropower dam play a critical role in social-economic development and ensure ...
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Ponencia
Descubriendo Reglas de Asociación Numéricas entre Series Temporales
Martínez Ballesteros, María del Mar; Martínez Álvarez, Francisco; Troncoso Lora, Alicia; Riquelme Santos, José Cristóbal (Universidad de Sevilla, 2009)Este trabajo presenta el descubrimiento de reglas de asociación basadas en técnicas evolutivas para obtener relaciones ...
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Capítulo de Libro
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)Breast cancer is one of the diseases causing the largest number of deaths among women. Its early detection has been proved ...
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Artículo
DIAFAN-TL: An instance weighting-based transfer learning algorithm with application to phenology forecasting
Molina Cabanillas, Miguel Ángel; Jiménez Navarro, Manuel Jesús; Arjona, Ricardo; Martínez Álvarez, Francisco; Asencio Cortés, Gualberto (ScienceDirect, 2022-10)The agricultural sector has been, and still is, the most important economic sector in many countries. Due to advances in ...
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Ponencia
Discovering Spatio-Temporal Patterns in Precision Agriculture Based on Triclustering
Melgar García, Laura; Godinho, María Teresa; Espada, Rita; Gutiérrez Avilés, David; Brito, Isabel Sofía; Martínez Álvarez, Francisco; Troncoso Lora, Alicia; Rubio Escudero, Cristina (Springer, 2020)Agriculture has undergone some very important changes over the last few decades. The emergence and evolution of precision ...
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Artículo
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)The forecasting process of real-world time series has to deal with especially unexpected values, commonly known as outliers. ...
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Artículo
Earthquake magnitude prediction based on arti cial neural networks: a survey
Morales Esteban, Antonio; Florido, Emilio; Aznarte, José Luis; Martínez Álvarez, Francisco (Croatian Operational Research Society, 2016)The occurrence of earthquakes has been studied from many aspects. Apparently, earthquakes occur without warning and can ...
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Ponencia
Embedded Temporal Feature Selection for Time Series Forecasting Using Deep Learning
Jiménez Navarro, Manuel Jesús; Martínez Ballesteros, María del Mar; Martínez Álvarez, Francisco; Asencio Cortés, Gualberto (Springer Link, 2023-10)Traditional time series forecasting models often use all available variables, including potentially irrelevant or noisy ...
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Artículo
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)This paper presents a new approach to forecast the behavior of time series based on similarity of pattern sequences. ...
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Ponencia
Evaluación de biclusters en un entorno evolutivo
Pontes Balanza, Beatriz; Giráldez, Raúl; Divina, Federico; Martínez Álvarez, Francisco (Thomson, 2007)La mayoría de las heurísticas utilizadas para la búsqueda de biclusters en microarrays hacen uso del residuo cuadrático ...
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Ponencia
Evaluación de biclusters mediante intra-fluctuaciones mínimas: un enfoque multi-objetivo
Pontes Balanza, Beatriz; Giráldez, Raúl; Divina, Federico; Martínez Álvarez, Francisco (2007)Las técnicas de biclustering aplicadas a datos de expresión génica persiguen la extracción de subconjuntos de genes ...
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Ponencia
Evolutionary computation to explain deep learning models for time series forecasting
Troncoso García, Ángela del Robledo; Martínez Ballesteros, María del Mar; Martínez Álvarez, Francisco; Troncoso Lora, Alicia (Association for Computing Machinery, 2023-06)Deep learning has become one of the most useful tools in the last years to mine information from large datasets. Despite ...
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Artículo
Explainable machine learning for sleep apnea prediction
Troncoso García, Ángela del Robledo; Martínez Ballesteros, María del Mar; Martínez Álvarez, Francisco; Troncoso Lora, Alicia (ScienceDirect, 2022)Machine and deep learning has become one of the most useful tools in the last years as a diagnosis-decision-support tool ...
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Artículo
Explaining deep learning models for ozone pollution prediction via embedded feature selection
Jiménez Navarro, Manuel Jesús; Martínez Ballesteros, María del Mar; Martínez Álvarez, Francisco; Asencio Cortés, Gualberto (ScienceDirect, 2024)Ambient air pollution is a pervasive global issue that poses significant health risks. Among pollutants, ozone (O3) is ...
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Ponencia
Explaining Learned Patterns in Deep Learning by Association Rules Mining
Jiménez Navarro, Manuel Jesús; Martínez Ballesteros, María del Mar; Martínez Álvarez, Francisco; Asencio Cortés, Gualberto (SpringerLink, 2023-08)This paper proposes a novel approach that combines an association rule algorithm with a deep learning model to enhance the ...
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Ponencia
Feature-Aware Drop Layer (FADL): A Nonparametric Neural Network Layer for Feature Selection
Jiménez Navarro, Manuel Jesús; Martínez Ballesteros, María del Mar; Sousa Brito, Isabel Sofía; Martínez Álvarez, Francisco; Asencio Cortés, Gualberto (SpringerLink, 2022)Neural networks have proven to be a good alternative in application fields such as healthcare, time-series forecasting and ...
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Artículo
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)This work aims at correcting flaws existing in multi-objective evolutionary schemes to discover quantitative association ...
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Capítulo de Libro
Improving Time Series Forecasting by Discovering Frequent Episodes in Sequences
Martínez Álvarez, Francisco; Troncoso Lora, Alicia; Riquelme Santos, José Cristóbal (2009)This work aims to improve an existing time series forecasting algorithm –LBF– by the application of frequent episodes ...
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Capítulo de Libro
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)A new approach is presented in this work with the aim of predicting time series behaviors. A previous labeling of the ...
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Artículo
Mining quantitative association rules based on evolutionary computation and its application to atmospheric pollution
Martínez Ballesteros, María del Mar; Troncoso Lora, Alicia; Martínez Álvarez, Francisco; Riquelme Santos, José Cristóbal (IOS Press, 2010)This research presents the mining of quantitative association rules based on evolutionary computation techniques. First, ...