Publications Listing

SCI2S Publications (D. García-Gil)

Number of Results: 14

Jump to Year: 2023, 2021, 2019, 2018, 2017

[3070] I. Aguilera-Martos, M. García-Bárzana, D. García-Gil, J. Carrasco, D. López, J. Luengo, F. Herrera. Multi-step histogram based outlier scores for unsupervised anomaly detection: ArcelorMittal engineering dataset case of study. Neurocomputing 544, 126228. doi: 10.1016/j.neucom.2023.126228
[3071] D. López, I. Aguilera-Martos, M. García-Bárzana, F. Herrera, D. García-Gil, J. Luengo. Fusing anomaly detection with false positive mitigation methodology for predictive maintenance under multivariate time series. Information Fusion 100, 101957. doi: 10.1016/j.inffus.2023.101957

[3078] J. Carrasco, D. López, I. Aguilera-Martos, D. García-Gil, I. Markova, M. García-Bárzana, M. Arias-Rodil, J. Luengo, F. Herrera. Anomaly detection in predictive maintenance: A new evaluation framework for temporal unsupervised anomaly detection algorithms. Neurocomputing 462: 440-452 (2021). doi: 10.1016/j.neucom.2021.07.095

[2543] I. Triguero, D. García-Gil, J. Maillo, J. Luengo, S. García, F. Herrera. Transforming big data into smart data: An insight on the use of the k nearest neighbors algorithm to obtain quality data. Wiley Interdisciplinary Reviews. Data Mining and Knowledge Discovery. e1289. doi: 10.1002/widm.1289
[2557] D. García-Gil, J. Luengo, S. García, F. Herrera. Enabling smart data: noise filtering in big data classification. Information Sciences 479, 135-152. doi: 10.1016/j.ins.2018.12.002
[3088] D. García-Gil, F. Luque Sánchez, J. Luengo, S. García, F. Herrera. From Big to Smart Data: Iterative ensemble filter for noise filtering in Big Data classification. International Journal of Intelligent Systems 34(12): 3260-3274 (2019). doi: 10.1002/int.22193
[3091] B. Montesdeoca, J. Luengo, J. Maillo, D. García-Gil, S. García, F. Herrera. A First Approach on Big Data Missing Values Imputation. IoTBDS 2019: 315-323. doi: 10.5220/0007738403150323
[3092] D. García-Gil, A. Alcalde-Barros, J. Luengo, S. García, F. Herrera. Big Data Preprocessing as the Bridge between Big Data and Smart Data: BigDaPSpark and BigDaPFlink Libraries. IoTBDS 2019: 324-331. doi: 10.5220/0007738503240331

[2462] D. Martín, M. Martínez-Ballesteros, D. García-Gil, J. Alcalá-Fdez, J.C. Riquelme-Santos, F. Herrera. MRQAR: a generic MapReduce framework to discover Quantitative Association Rules in Big Data problems. Knowledge-Based Systems 153 (2018) 176-192. doi: 10.1016/j.knosys.2018.04.037
[2580] D. García-Gil, S. Ramírez-Gallego, S. García, F. Herrera. Principal Components Analysis Random Discretization Ensemble for Big Data. Knowledge-Based Systems, 150, 2018, 166-174. doi: 10.1016/j.knosys.2018.03.012
[2581] D. García-Gil, S. Ramírez-Gallego, S. García, F. Herrera. On the Use of Random Discretization and Dimensionality Reduction in Ensembles for Big Data. International Conference on Hybrid Artificial Intelligence Systems, 2018, 15-26. doi: 10.1007/978-3-319-92639-1_2
[2582] L. Pereyra, D. García-Gil, F. Herrera, LC. González-Gurrola, J. Carrasco, MA Medina-Pérez, R Monroy. Bagging-RandomMiner-Un Algoritmo en MapReduce para Detección de Anomalías en Big Data. XVIII Conferencia de la Asociación Española para la Inteligencia Artificial (CAEPIA2018), II Workshop en Big Data y Análisis de Datos Escalable , Octubre 23-26, 2018.
[2583] D. García-Gil, J. Luengo, S. García, F. Herrera. Smart Data: Filtrado de Ruido para Big Data. XVIII Conferencia de la Asociación Española para la Inteligencia Artificial (CAEPIA2018), II Workshop en Big Data y Análisis de Datos Escalable, Octubre 23-26, 2018.

[2160] D. García-Gil, S. Ramírez-Gallego, S. García, F. Herrera. A comparison on scalability for batch big data processing on Apache Spark and Apache Flink. Big Data Analytics 2:1 (2017) 1. doi: 10.1186/s41044-016-0020-2