CRISTÓBAL JOSÉ
CARMONA DEL JESÚS
TITULAR DE UNIVERSIDAD
ÁNGEL MIGUEL
GARCÍA VICO
Researcher in the period 2020-2021
Publications by the researcher in collaboration with ÁNGEL MIGUEL GARCÍA VICO (25)
2024
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Advancing Computational Frontiers: Spiking Neural Networks in High-Energy Efficiency Computing Across Diverse Domains
Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
2023
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A Multiclustering Evolutionary Hyperrectangle-Based Algorithm
International Journal of Computational Intelligence Systems, Vol. 16, Núm. 1
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A distributed evolutionary fuzzy system-based method for the fusion of descriptive emerging patterns in data streams
Information Fusion, Vol. 91, pp. 412-423
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An Evolutionary Fuzzy System for Multiclustering in Data Streaming
Procedia Computer Science
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Clustering: an R library to facilitate the analysis and comparison of cluster algorithms
Progress in Artificial Intelligence, Vol. 12, Núm. 1, pp. 33-44
2022
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A Case of Study with the Clustering R Library to Measure the Quality of Cluster Algorithms
Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
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Gamificación mediante juegos de bloques en asignaturas del ámbito de la Inteligencia Artificial en el Grado en Ingeniería Informática
Educar para transformar: Innovación pedagógica, calidad y TIC en contextos formativos (Dykinson), pp. 1076-1082
2021
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A Preliminary Many Objective Approach for Extracting Fuzzy Emerging Patterns
Advances in Intelligent Systems and Computing
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A Preliminary Many Objective Approach for Extracting Fuzzy Emerging Patterns
15th International Conference on Soft Computing Models in Industrial and Environmental Applications (SOCO 2020): Burgos, Spain ; September 2020
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A cellular-based evolutionary approach for the extraction of emerging patterns in massive data streams
Expert Systems with Applications, Vol. 183
2020
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E2PAMEA: A fast evolutionary algorithm for extracting fuzzy emerging patterns in big data environments
Neurocomputing, Vol. 415, pp. 60-73
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FEPDS: A Proposal for the Extraction of Fuzzy Emerging Patterns in Data Streams
IEEE Transactions on Fuzzy Systems, Vol. 28, Núm. 12, pp. 3193-3203
2019
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A Big Data Approach for the Extraction of Fuzzy Emerging Patterns
Cognitive Computation, Vol. 11, Núm. 3, pp. 400-417
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Subgroup discovery on multiple instance data
International Journal of Computational Intelligence Systems, Vol. 12, Núm. 2, pp. 1602-1612
2018
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An overview of emerging pattern mining in supervised descriptive rule discovery: taxonomy, empirical study, trends, and prospects
Wiley Interdisciplinary Reviews: Data Mining and Knowledge Discovery, Vol. 8, Núm. 1
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Improvement of subgroup descriptions in noisy data by detecting exceptions
Progress in Artificial Intelligence, Vol. 7, Núm. 1, pp. 55-64
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MOEA-EFEP: Multi-Objective Evolutionary Algorithm for Extracting Fuzzy Emerging Patterns
IEEE Transactions on Fuzzy Systems, Vol. 26, Núm. 5, pp. 2861-2872
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MOEA-EFEP: un algoritmo evolutivo multi-objetivo para la extracción de patrones emergentes difusos
XVIII Conferencia de la Asociación Española para la Inteligencia Artificial (CAEPIA 2018): avances en Inteligencia Artificial. 23-26 de octubre de 2018 Granada, España
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Modelos descriptivos basados en aprendizaje supervisado para el tratamiento de grandes vol´umenes de datos y flujos continuos de datos
XVIII Conferencia de la Asociación Española para la Inteligencia Artificial (CAEPIA 2018): avances en Inteligencia Artificial. 23-26 de octubre de 2018 Granada, España
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Una primera aproximación para la extracción de patrones emergentes en flujos continuos de datos
XVIII Conferencia de la Asociación Española para la Inteligencia Artificial (CAEPIA 2018): avances en Inteligencia Artificial. 23-26 de octubre de 2018 Granada, España