D. Urda

发表

Application of genetic algorithms and constructive neural networks for the analysis of microarray cancer data

R. M. Luque-Baena, L. Franco, J. M. Jerez, 2014, Theoretical Biology and Medical Modelling.

Improving the Reliability of Network Intrusion Detection Systems Through Dataset Integration

B. Dorronsoro, D. Urda, Roberto Mag'an-Carri'on, 2021, IEEE Transactions on Emerging Topics in Computing.

A permutation entropy-based EMD–ANN forecasting ensemble approach for wind speed prediction

J. J. Ruiz-Aguilar, I. Turias, J. González-Enrique, 2020, Neural Computing and Applications.

Artificial Neural Networks, Sequence-to-Sequence LSTMs, and Exogenous Variables as Analytical Tools for NO2 (Air Pollution) Forecasting: A Case Study in the Bay of Algeciras (Spain)

José Antonio Moscoso López, J. J. Ruiz-Aguilar, I. Turias, 2021, Sensors.

A comparison of ranking filter methods applied to the estimation of NO2 concentrations in the Bay of Algeciras (Spain)

J. J. Ruiz-Aguilar, I. Turias, J. González-Enrique, 2021, Stochastic Environmental Research and Risk Assessment.

Hourly Air Quality Index (AQI) Forecasting Using Machine Learning Methods

Daniel Urda, José Antonio Moscoso López, Juan Jesús Ruiz-Aguilar, 2020, SOCO.

A permutation entropy-based EMD–ANN forecasting ensemble approach for wind speed prediction

D. Urda, J. J. Ruiz-Aguilar, I. Turias, 2020, Neural Computing and Applications.

Ro-Ro Freight Prediction Using a Hybrid Approach Based on Empirical Mode Decomposition, Permutation Entropy and Artificial Neural Networks

Daniel Urda, Héctor Mesa, José Antonio Moscoso López, 2019, HAIS.

A Genetic Algorithm and Neural Network Stacking Ensemble Approach to Improve NO2 Level Estimations

Daniel Urda, José Antonio Moscoso López, Ignacio J. Turias, 2019, IWANN.

Ro-Ro Freight Forecasting Based on an ANN-SVR Hybrid Approach. Case of the Strait of Gibraltar

Daniel Urda, José Antonio Moscoso López, Juan Jesús Ruiz-Aguilar, 2019, IWANN.

Advanced Machine Learning Techniques for Fake News (Online Disinformation) Detection: A Systematic Mapping Study pdf

Daniel Urda, Konstantina Remoundou, Michal Choras, 2020, Appl. Soft Comput..

A freight inspection volume forecasting approach using an aggregation/disaggregation procedure, machine learning and ensemble models

Daniel Urda, José Antonio Moscoso López, Juan Jesús Ruiz-Aguilar, 2020, Neurocomputing.

Advanced Online Survival Analysis Tool for Predictive Modelling in Clinical Data Science

Daniel Urda, José Luis Subirats, Emilio Alba, 2016, PloS one.

Application of genetic algorithms and constructive neural networks for the analysis of microarray cancer data

R. M. Luque-Baena, L. Franco, J. M. Jerez, 2014, Theoretical Biology and Medical Modelling.

Analysis of Cancer Microarray Data using Constructive Neural Networks and Genetic Algorithms

Rafael Marcos Luque Baena, Daniel Urda, Leonardo Franco, 2013, IWBBIO.

Constructive Neural Networks to Predict Breast Cancer Outcome by Using Gene Expression Profiles

Daniel Urda, Leonardo Franco, José Luis Subirats, 2010, IEA/AIE.

Robust gene signatures from microarray data using genetic algorithms enriched with biological pathway keywords

M. Gonzalo Claros, Rafael Marcos Luque Baena, Daniel Urda, 2014, J. Biomed. Informatics.

IgG glycan patterns are associated with type 2 diabetes in independent European populations.

F. Agakov, I. Rudan, C. Hayward, 2017, Biochimica et biophysica acta. General subjects.

Forward Noise Adjustment Scheme for Data Augmentation

Daniel Urda, José M. Jerez, Leonardo Franco, 2018, 2018 IEEE Symposium Series on Computational Intelligence (SSCI).

Efficient Implementation of the Backpropagation Algorithm in FPGAs and Microcontrollers

Rafael Marcos Luque Baena, Daniel Urda, Leonardo Franco, 2016, IEEE Transactions on Neural Networks and Learning Systems.

A Clustering-Based Hybrid Support Vector Regression Model to Predict Container Volume at Seaport Sanitary Facilities

Daniel Urda, Juan Jesús Ruiz-Aguilar, Javier González-Enrique, 2020, Applied Sciences.

Trends and Patterns of International Student Mobility: The Case of Bachelor's Degrees in Computer Science at the University of Burgos

Ángel Arroyo, Á. Herrero, Secil Bayraktar, 2020, ICEUTE.

Towards a Reliable Comparison and Evaluation of Network Intrusion Detection Systems Based on Machine Learning Approaches

Bernabé Dorronsoro, Daniel Urda, Roberto Magán-Carrión, 2020, Applied Sciences.

Combining feature engineering and feature selection to improve the prediction of methionine oxidation sites in proteins

Daniel Urda, José Luis Subirats, Francisco J. Veredas, 2018, Neural Computing and Applications.

BLASSO: integration of biological knowledge into a regularized linear model

M. Gonzalo Claros, Daniel Urda, Leonardo Franco, 2018, BMC Systems Biology.

Machine learning models to search relevant genetic signatures in clinical context

Rafael Marcos Luque Baena, Daniel Urda, Noelia Sánchez-Maroño, 2017, 2017 International Joint Conference on Neural Networks (IJCNN).

WIMP: Web server tool for missing data imputation

D. Urda, J.L. Subirats, P.J. García-Laencina, 2012, Comput. Methods Programs Biomed..

Optimization and Learning: Third International Conference, OLA 2020, Cádiz, Spain, February 17–19, 2020, Proceedings

Krishna M. Sivalingam, Alfredo Cuzzocrea, Simone Diniz Junqueira Barbosa, 2020, OLA.

Hourly pollutants forecasting using a deep learning approach to obtain the AQI

José Antonio Moscoso López, J. J. Ruiz-Aguilar, I. Turias, 2023, Log. J. IGPL.

A machine learning-based forecasting system of perishable cargo flow in maritime transport

Daniel Urda, José Antonio Moscoso López, Juan Jesús Ruiz-Aguilar, 2020, Neurocomputing.

MetODeep: A Deep Learning Approach for Prediction of Methionine Oxidation Sites in Proteins

Daniel Urda, José M. Jerez, Francisco J. Veredas, 2019, 2019 International Joint Conference on Neural Networks (IJCNN).

Addressing critical issues in the development of an Oncology Information System

Daniel Urda, Leonardo Franco, José Luis Subirats, 2013, Int. J. Medical Informatics.

Classification of high dimensional data using LASSO ensembles

Daniel Urda, Leonardo Franco, José M. Jerez, 2017, 2017 IEEE Symposium Series on Computational Intelligence (SSCI).

Learning Variables Structure Using Evolutionary Algorithms to Improve Predictive Performance

Bernabé Dorronsoro, Daniel Urda, Ignacio J. Turias, 2020, OLA.