Daniel Urda

发表

Storing Location-Aware Data in Mobile Distributed Systems

Ciprian Dobre, Florin Pop, Daniel Urda, 2013, 2013 IEEE 12th International Symposium on Parallel and Distributed Computing.

A Machine Learning Approach to Determine Abundance of Inclusions in Stainless Steel

Daniel Urda, Héctor Mesa, Juan J. Ruiz-Aguilar, 2019, HAIS.

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 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.

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.

Use of q-values to Improve a Genetic Algorithm to Identify Robust Gene Signatures

Paulo J. G. Lisboa, Daniel Urda, Ian H. Jarman, 2014, CIBB.

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.

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.

Addition of Pathway-Based Information to Improve Predictions in Transcriptomics

Daniel Urda, Leonardo Franco, Francisco J. Veredas, 2019, IWBBIO.

Forward Noise Adjustment Scheme for Data Augmentation

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

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 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.

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).

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

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

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

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

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.

Container Demand Forecasting at Border Posts of Ports: A Hybrid SARIMA-SOM-SVR Approach

Daniel Urda, José Antonio Moscoso López, Ignacio J. Turias, 2020, OLA.

L_1 L 1 -regularization Model Enriched with Biological Knowledge

Daniel Urda, Leonardo Franco, José M. Jerez, 2017, IWBBIO.

Deep Learning to Analyze RNA-Seq Gene Expression Data

Daniel Urda, José M. Jerez, Leonardo Franco, 2017, IWANN.

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

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

Learning Variables Structure Using Evolutionary Algorithms to Improve Predictive Performance

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

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

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

BLASSO: integration of biological knowledge into a regularized linear model

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

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.

A Constructive Neural Network to Predict Pitting Corrosion Status of Stainless Steel

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

Data Dimension and Structure Effects in Predictive Performance of Deep Neural Networks

Daniel Urda, Ignacio J. Turias, José M. Jerez, 2018, SoMeT.

Committee C-Mantec: A Probabilistic Constructive Neural Network

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

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).

Beta-Hebbian Learning for Visualizing Intrusions in Flows

Héctor Quintián-Pardo, José Luís Casteleiro-Roca, Esteban Jove, 2020, CISIS.

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.

Hybrid (Generalization-Correlation) Method for Feature Selection in High Dimensional DNA Microarray Prediction Problems

Daniel Urda, Leonardo Franco, José Luis Subirats, 2011, IWANN.

Classification of high dimensional data using LASSO ensembles

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

Addressing critical issues in the development of an Oncology Information System

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

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.

Advanced 3D Visualization of Android Malware Families

Héctor Quintián-Pardo, José Luís Calvo-Rolle, Álvaro Herrero, 2021, CISIS-ICEUTE.

Improving the Reliability of Network Intrusion Detection Systems through Dataset Integration pdf

Daniel Urda, Roberto Mag'an-Carri'on, Ignacio D'iaz-Cano, 2021, ArXiv.

Assessing the Impact of Batch-Based Data Aggregation Techniques for Feature Engineering on Machine Learning-Based Network IDSs

Bernabé Dorronsoro, Daniel Urda, Roberto Magán-Carrión, 2021, CISIS-ICEUTE.

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.

Deep neural networks architecture driven by problem-specific information

Daniel Urda, Javier González-Enrique, Francisco J. Veredas, 2021, Neural Computing and Applications.