Gualberto
Asencio Cortés
Universidad de Sevilla
Sevilla, EspañaPublications in collaboration with researchers from Universidad de Sevilla (23)
2024
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Explaining deep learning models for ozone pollution prediction via embedded feature selection
Applied Soft Computing, Vol. 157
2023
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A bioinspired ensemble approach for multi-horizon reference evapotranspiration forecasting in Portugal
Proceedings of the ACM Symposium on Applied Computing
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A new deep learning architecture with inductive bias balance for transformer oil temperature forecasting
Journal of Big Data, Vol. 10, Núm. 1
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Embedded Temporal Feature Selection for Time Series Forecasting Using Deep Learning
Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
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Explaining Learned Patterns in Deep Learning by Association Rules Mining
Lecture Notes in Networks and Systems
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Feature-Aware Drop Layer (FADL): A Nonparametric Neural Network Layer for Feature Selection
Lecture Notes in Networks and Systems
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PHILNet: A novel efficient approach for time series forecasting using deep learning
Information Sciences, Vol. 632, pp. 815-832
2022
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Automatic Eligibility of Sellers in an Online Market Place: A Case Study of Amazon Algorithm
Information (Switzerland), Vol. 13, Núm. 2
2021
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A Preliminary Study on Deep Transfer Learning Applied to Image Classification for Small Datasets
Advances in Intelligent Systems and Computing
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A Preliminary Study on Deep Transfer Learning Applied to Image Classification for Small Datasets
15th International Conference on Soft Computing Models in Industrial and Environmental Applications (SOCO 2020): Burgos, Spain ; September 2020
2020
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Coronavirus Optimization Algorithm: A Bioinspired Metaheuristic Based on the COVID-19 Propagation Model
Big data, Vol. 8, Núm. 4, pp. 308-322
2019
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A novel ensemble method for electric vehicle power consumption forecasting: Application to the Spanish system
IEEE Access, Vol. 7, pp. 120840-120856
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Impact of Auto-evaluation Tests as Part of the Continuous Evaluation in Programming Courses
Advances in Intelligent Systems and Computing
2018
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A novel approach to forecast urban surface-level ozone considering heterogeneous locations and limited information
Environmental Modelling and Software, pp. 52-61
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A novel tree-based algorithm to discover seismic patterns in earthquake catalogs
Computers and Geosciences, Vol. 115, pp. 96-104
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Data field-based K-means clustering for spatio-temporal seismicity analysis and hazard assessment
Remote Sensing, Vol. 10, Núm. 3
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Earthquake prediction in California using regression algorithms and cloud-based big data infrastructure
Computers and Geosciences, Vol. 115, pp. 198-210
2017
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Comparing seismic parameters for different source zone models in the Iberian Peninsula
Tectonophysics, Vol. 717, pp. 449-472
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Medium–large earthquake magnitude prediction in Tokyo with artificial neural networks
Neural Computing and Applications, Vol. 28, Núm. 5, pp. 1043-1055
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Using principal component analysis to improve earthquake magnitude prediction in Japan
Logic Journal of the IGPL, Vol. 25, Núm. 6, pp. 949-966