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José García-Nieto
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2020 – today
- 2024
- [j45]Adrián Segura-Ortiz
, José García-Nieto
Multi-objective context-guided consensus of a massive array of techniques for the inference of Gene Regulatory Networks. Comput. Biol. Medicine 179: 108850 (2024) - [j44]Hossein Nematzadeh
Pattern recognition frequency-based feature selection with multi-objective discrete evolution strategy for high-dimensional medical datasets. Expert Syst. Appl. 249: 123521 (2024) - [j43]Hossein Nematzadeh
Feature selection using a classification error impurity algorithm and an adaptive genetic algorithm improved with an external repository. Knowl. Based Syst. 301: 112345 (2024) - [j42]Marco Dorigo, Heiko Hamann, Manuel López-Ibáñez, José García-Nieto, Andries P. Engelbrecht, Carlo Pinciroli, Volker Strobel, Christian Leonardo Camacho-Villalón:
Ants 2022 special issue. Swarm Intell. 18(2): 101-103 (2024) - [j41]Antonio J. Nebro, Manuel López-Ibáñez, José García-Nieto
On the automatic design of multi-objective particle swarm optimizers: experimentation and analysis. Swarm Intell. 18(2): 105-139 (2024) - [c32]Adrián Segura-Ortiz
Exploiting Medical-Expert Knowledge Via a Novel Memetic Algorithm for the Inference of Gene Regulatory Networks. ICCS (4) 2024: 3-17 - 2023
- [j40]Hossein Nematzadeh
Ensemble-based genetic algorithm explainer with automized image segmentation: A case study on melanoma detection dataset. Comput. Biol. Medicine 155: 106613 (2023) - [j39]Adrián Segura-Ortiz
GENECI: A novel evolutionary machine learning consensus-based approach for the inference of gene regulatory networks. Comput. Biol. Medicine 155: 106653 (2023) - [j38]Manuel Paneque
e-LION: Data integration semantic model to enhance predictive analytics in e-Learning. Expert Syst. Appl. 213(Part): 118892 (2023) - 2022
- [j37]Hossein Nematzadeh
Automatic frequency-based feature selection using discrete weighted evolution strategy. Appl. Soft Comput. 130: 109699 (2022) - [j36]José F. Aldana-Martín, José García-Nieto, María del Mar Roldán García, José Francisco Aldana Montes:
Semantic modelling of Earth Observation remote sensing. Expert Syst. Appl. 187: 115838 (2022) - [c31]Daniel Doblas, Antonio J. Nebro
Automatic Design of Multi-objective Particle Swarm Optimizers. ANTS Conference 2022: 28-40 - [c30]Sandro Hurtado
A Service for Flexible Management and Analysis of Heterogeneous Clinical Data. IWBBIO (1) 2022: 227-238 - [c29]Sandro Hurtado
On the Use of Explainable Artificial Intelligence for the Differential Diagnosis of Pigmented Skin Lesions. IWBBIO (1) 2022: 319-329 - [e1]Marco Dorigo
Swarm Intelligence - 13th International Conference, ANTS 2022, Málaga, Spain, November 2-4, 2022, Proceedings. Lecture Notes in Computer Science 13491, Springer 2022, ISBN 978-3-031-20175-2 [contents] - 2021
- [j35]Sandro Hurtado
Reconstruction of gene regulatory networks with multi-objective particle swarm optimisers. Appl. Intell. 51(4): 1972-1991 (2021) - [j34]Sandro Hurtado
FIMED: Flexible management of biomedical data. Comput. Methods Programs Biomed. 212: 106496 (2021) - [j33]Cristóbal Barba-González, Antonio J. Nebro, José García-Nieto
Injecting domain knowledge in multi-objective optimization problems: A semantic approach. Comput. Stand. Interfaces 78: 103546 (2021) - [j32]María del Mar Roldán García
Ontology-driven approach for KPI meta-modelling, selection and reasoning. Int. J. Inf. Manag. 58: 102018 (2021) - [j31]Antonio Benítez-Hidalgo
TITAN: A knowledge-based platform for Big Data workflow management. Knowl. Based Syst. 232: 107489 (2021) - 2020
- [j30]Cristóbal Barba-González
On the design of a framework integrating an optimization engine with streaming technologies. Future Gener. Comput. Syst. 107: 538-550 (2020) - [j29]Cristóbal Barba-González, Antonio J. Nebro
A multi-objective interactive dynamic particle swarm optimizer. Prog. Artif. Intell. 9(1): 55-65 (2020) - [j28]Esteban López-Camacho, María Jesús García-Godoy
Optimizing ligand conformations in flexible protein targets: a multi-objective strategy. Soft Comput. 24(14): 10705-10719 (2020)
2010 – 2019
- 2019
- [j27]María Jesús García-Godoy, Esteban López-Camacho, José García-Nieto
Bio-inspired optimization for the molecular docking problem: State of the art, recent results and perspectives. Appl. Soft Comput. 79: 30-45 (2019) - [j26]Ismael Navas-Delgado
VIGLA-M: visual gene expression data analytics. BMC Bioinform. 20-S(4): 150:1-150:11 (2019) - [j25]José García-Nieto
Inference of gene regulatory networks with multi-objective cellular genetic algorithm. Comput. Biol. Chem. 80: 409-418 (2019) - [j24]Cristóbal Barba-González, José García-Nieto
BIGOWL: Knowledge centered Big Data analytics. Expert Syst. Appl. 115: 543-556 (2019) - [j23]Uferah Shafi
Precision Agriculture Techniques and Practices: From Considerations to Applications. Sensors 19(17): 3796 (2019) - [j22]José García-Nieto
Multi-objective ligand-protein docking with particle swarm optimizers. Swarm Evol. Comput. 44: 439-452 (2019) - [j21]Antonio Benítez-Hidalgo
jMetalPy: A Python framework for multi-objective optimization with metaheuristics. Swarm Evol. Comput. 51 (2019) - [c28]Antonio J. Nebro
Automatic configuration of NSGA-II with jMetal and irace. GECCO (Companion) 2019: 1374-1381 - [i2]Antonio Benítez-Hidalgo, Antonio J. Nebro, José García-Nieto, Izaskun Oregi, Javier Del Ser:
jMetalPy: a Python Framework for Multi-Objective Optimization with Metaheuristics. CoRR abs/1903.02915 (2019) - 2018
- [j20]Cristóbal Barba-González, José García-Nieto
jMetalSP: A framework for dynamic multi-objective big data optimization. Appl. Soft Comput. 69: 737-748 (2018) - [j19]Antonio J. Nebro
InDM2: Interactive Dynamic Multi-Objective Decision Making Using Evolutionary Algorithms. Swarm Evol. Comput. 40: 184-195 (2018) - [c27]Antonio Benítez-Hidalgo
About Designing an Observer Pattern-Based Architecture for a Multi-objective Metaheuristic Optimization Framework. IDC 2018: 50-60 - [c26]Cristóbal Barba-González, José García-Nieto
Scalable Inference of Gene Regulatory Networks with the Spark Distributed Computing Platform. IDC 2018: 61-70 - [c25]Cristóbal Barba-González, Vesa Ojalehto, José García-Nieto
Artificial Decision Maker Driven by PSO: An Approach for Testing Reference Point Based Interactive Methods. PPSN (1) 2018: 274-285 - [c24]Antonio J. Nebro
Extending the Speed-Constrained Multi-objective PSO (SMPSO) with Reference Point Based Preference Articulation. PPSN (1) 2018: 298-310 - 2017
- [j18]Cristian Zambrano-Vega
M2Align: parallel multiple sequence alignment with a multi-objective metaheuristic. Bioinform. 33(19): 3011-3017 (2017) - [j17]María del Mar Roldán García
Enhancing semantic consistency in anti-fraud rule-based expert systems. Expert Syst. Appl. 90: 332-343 (2017) - [j16]Cristian Zambrano-Vega
Multiple Sequence Alignment with Multiobjective Metaheuristics. A Comparative Study. Int. J. Intell. Syst. 32(8): 843-861 (2017) - [j15]Cristian Zambrano-Vega
Comparing multi-objective metaheuristics for solving a three-objective formulation of multiple sequence alignment. Prog. Artif. Intell. 6(3): 195-210 (2017) - [c23]Cristóbal Barba-González, José García-Nieto
Multi-objective Big Data Optimization with jMetal and Spark. EMO 2017: 16-30 - [c22]Antonio J. Nebro
Design and architecture of the jMetaISP framework. GECCO (Companion) 2017: 1239-1246 - [c21]Cristian Zambrano-Vega
A Multi-objective Optimization Framework for Multiple Sequence Alignment with Metaheuristics. IWBBIO (2) 2017: 245-256 - 2016
- [j14]María del Mar Roldán García
An ontology-based data integration approach for web analytics in e-commerce. Expert Syst. Appl. 63: 20-34 (2016) - [j13]Cristóbal Barba-González, José García-Nieto
A Fine Grain Sentiment Analysis with Semantics in Tweets. Int. J. Interact. Multim. Artif. Intell. 3(6): 22-28 (2016) - [c20]Esteban López-Camacho
A New Multi-objective Approach for Molecular Docking Based on RMSD and Binding Energy. AlCoB 2016: 65-77 - [c19]José García-Nieto
A Study of Archiving Strategies in Multi-objective PSO for Molecular Docking. ANTS Conference 2016: 40-52 - [c18]José A. Cordero, Antonio J. Nebro
Dynamic Multi-Objective Optimization with jMetal and Spark: A Case Study. MOD 2016: 106-117 - [c17]Maciej Rybinski, María del Mar Roldán García, José García-Nieto, José Francisco Aldana Montes:
DisMatch results for OAEI 2016. OM@ISWC 2016: 161-165 - 2015
- [j12]Ana Carolina Olivera
Reducing vehicle emissions and fuel consumption in the city by using particle swarm optimization. Appl. Intell. 42(3): 389-405 (2015) - [j11]Esteban López-Camacho
Solving molecular flexible docking problems with metaheuristics: A comparative study. Appl. Soft Comput. 28: 379-393 (2015) - [j10]José García-Nieto
Hybrid PSO6 for hard continuous optimization. Soft Comput. 19(7): 1843-1861 (2015) - 2014
- [j9]Javier Apolloni, José García-Nieto
Empirical evaluation of distributed Differential Evolution on standard benchmarks. Appl. Math. Comput. 236: 351-366 (2014) - [c16]José García-Nieto
Optimising traffic lights with metaheuristics: Reduction of car emissions and consumption. IJCNN 2014: 48-54 - 2013
- [j8]José García-Nieto
Optimal Cycle Program of Traffic Lights With Particle Swarm Optimization. IEEE Trans. Evol. Comput. 17(6): 823-839 (2013) - 2012
- [j7]José García-Nieto
Parallel multi-swarm optimizer for gene selection in DNA microarrays. Appl. Intell. 37(2): 255-266 (2012) - [j6]José García-Nieto
Swarm intelligence for traffic light scheduling: Application to real urban areas. Eng. Appl. Artif. Intell. 25(2): 274-283 (2012) - [j5]Jamal Toutouh
Intelligent OLSR Routing Protocol Optimization for VANETs. IEEE Trans. Veh. Technol. 61(4): 1884-1894 (2012) - [c15]José García-Nieto
Why six informants is optimal in PSO. GECCO 2012: 25-32 - 2011
- [j4]José García-Nieto
Restart particle swarm optimization with velocity modulation: a scalability test. Soft Comput. 15(11): 2221-2232 (2011) - [c14]José García-Nieto
Empirical computation of the quasi-optimal number of informants in particle swarm optimization. GECCO 2011: 147-154 - [c13]José García-Nieto
Enhancing the urban road traffic with Swarm Intelligence: A case study of Córdoba city downtown. ISDA 2011: 368-373 - 2010
- [j3]José García-Nieto
Automatic tuning of communication protocols for vehicular ad hoc networks using metaheuristics. Eng. Appl. Artif. Intell. 23(5): 795-805 (2010) - [j2]Juan José Durillo
A Study of Multiobjective Metaheuristics When Solving Parameter Scalable Problems. IEEE Trans. Evol. Comput. 14(4): 618-635 (2010) - [c12]José García-Nieto
Automatic Parameter Tuning with Metaheuristics of the AODV Routing Protocol for Vehicular Ad-Hoc Networks. EvoApplications (2) 2010: 21-30 - [p1]Juan José Durillo
On the Velocity Update in Multi-Objective Particle Swarm Optimizers. Advances in Multi-Objective Nature Inspired Computing 2010: 45-62 - [i1]José García-Nieto, Enrique Alba:
Swarm Intelligence Approach for Accurate Gene Selection in DNA Microarrays. ERCIM News 2010(82): 26-27 (2010)
2000 – 2009
- 2009
- [j1]José García-Nieto
Sensitivity and specificity based multiobjective approach for feature selection: Application to cancer diagnosis. Inf. Process. Lett. 109(16): 887-896 (2009) - [c11]Antonio J. Nebro
SMPSO: A new PSO-based metaheuristic for multi-objective optimization. MCDM 2009: 66-73 - [c10]Juan José Durillo
Multi-Objective Particle Swarm Optimizers: An Experimental Comparison. EMO 2009: 495-509 - [c9]José García-Nieto, Enrique Alba, Javier Apolloni:
Noiseless functions black-box optimization: evaluation of a hybrid particle swarm with differential operators. GECCO (Companion) 2009: 2231-2238 - [c8]José García-Nieto, Enrique Alba, Javier Apolloni:
Particle swarm hybridized with differential evolution: black box optimization benchmarking for noisy functions. GECCO (Companion) 2009: 2343-2350 - 2008
- [c7]El-Ghazali Talbi, Laetitia Jourdan, José García-Nieto
Comparison of population based metaheuristics for feature selection: Application to microarray data classification. AICCSA 2008: 45-52 - [c6]Enrique Alba
New Research in Nature Inspired Algorithms for Mobility Management in GSM Networks. EvoWorkshops 2008: 1-10 - [c5]Javier Apolloni, Guillermo Leguizamón, José García-Nieto
Island Based Distributed Differential Evolution: An Experimental Study on Hybrid Testbeds. HIS 2008: 696-701 - 2007
- [c4]Enrique Alba
Gene selection in cancer classification using PSO/SVM and GA/SVM hybrid algorithms. IEEE Congress on Evolutionary Computation 2007: 284-290 - [c3]José García-Nieto
A comparison of PSO and GA approaches for gene selection and classification of microarray data. GECCO 2007: 427 - [c2]José García-Nieto
Using metaheuristic algorithms remotely via ROS. GECCO 2007: 1510 - 2006
- [c1]Enrique Alba, José García-Nieto, J. Francisco Chicano:
ROS: Servicio de Optimización Remota. JISBD 2006: 508-513
Coauthor Index
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