| Using multilayer fuzzy cognitive maps to diagnose autism spectrum disorder E Puerto, J Aguilar, C López, D Chávez Applied soft computing 75, 58-71, 2019 | 91 | 2019 |
| Recognition of the driving style in vehicle drivers J Cordero, J Aguilar, K Aguilar, D Chávez, E Puerto Sensors 20 (9), 2597, 2020 | 33 | 2020 |
| Microservices backlog-a model of granularity specification and microservice identification FH Vera-Rivera, EG Puerto-Cuadros, H Astudillo, CM Gaona-Cuevas Services Computing–SCC 2020: 17th International Conference, Held as Part of …, 2020 | 19 | 2020 |
| Learning algorithm for the recursive pattern recognition model EG Puerto Cuadros, JL Aguilar Castro Applied Artificial Intelligence 30 (7), 662-678, 2016 | 19 | 2016 |
| Un algoritmo recursivo de reconocimiento de patrones EG Puerto Cuadros, JL Aguilar Castro Revista Técnica de la Facultad de Ingeniería Universidad del Zulia 40 (2 …, 2017 | 16 | 2017 |
| Different Intelligent Approaches for Modeling the Style of Car Driving. J Aguilar, K Aguilar, D Chávez, J Cordero, E Puerto ICINCO (2), 284-291, 2017 | 16 | 2017 |
| Microservices backlog–A genetic programming technique for identification and evaluation of microservices from user stories FH Vera-Rivera, E Puerto, H Astudillo, CM Gaona IEEE Access 9, 117178-117203, 2021 | 15 | 2021 |
| A recursive patterns matching model for the dynamic pattern recognition problem E Puerto, J Aguilar, D Chávez Applied Artificial Intelligence 32 (4), 419-432, 2018 | 10 | 2018 |
| Automatic learning of ontologies for the Semantic Web: Experiment lexical learning E Puerto, J Aguilar, TR Chaparro Respuestas 17 (2), 5-12, 2012 | 10 | 2012 |
| Dynamic semantic ontological framework for web semantics T Rodriguez, E Puerto, J Aguilar Proceeding of the 9th WSEAS (CIMMACS’10, Mérida-Venezuela), 91-98, 2010 | 10 | 2010 |
| Formal description of a pattern for a recursive process of recognition E Puerto, J Aguilar 2016 IEEE Latin American Conference on Computational Intelligence (LA-CCI), 1-2, 2016 | 8 | 2016 |
| An Ar2p deep learning architecture for the discovery and the selection of features E Puerto, J Aguilar, R Vargas, J Reyes Neural Processing Letters 50, 623-643, 2019 | 7 | 2019 |
| Avances en el conocimiento y modelado computacional del cerebro autista: Una revisión de literatura EG Puerto Cuadros Cuaderno activa 9 (2017)), 109-125, 2017 | 5 | 2017 |
| Deep learning architecture for the recursive patterns recognition model E Puerto, J Aguilar, J Reyes, D Sarkar Journal of Physics: Conference Series 1126 (1), 012035, 2018 | 4 | 2018 |
| A new recursive patterns matching model inspired in systematic theory of human mind E Puerto, J Aguilar, D Chavez Int J Adv Comput Technol (IJACT) 9 (1), 28-39, 2017 | 4 | 2017 |
| Análisis de la teoría de la mente humana basada en el reconocimiento de patrones E Puerto, J Aguilar, B Perez Proceedings of the 2014 Congreso Internacional en Innovación y Apropiación …, 2014 | 4 | 2014 |
| A meta-learning architecture based on linked data R Dos Santos, J Aguilar, E Puerto 2021 XLVII Latin American Computing Conference (CLEI), 1-10, 2021 | 3 | 2021 |
| Emergence analysis in a Multi-robot System A Gil, J Aguilar, E Puerto, E Dapena 2018 XLIV Latin American Computer Conference (CLEI), 662-669, 2018 | 3 | 2018 |
| Detección de modos de transporte usando datos GPS MA Adarme Jaimes, D Heredia-Vizcaino, EG Puerto Cuadros Cuaderno activa 9 (2017)), 13-29, 2017 | 3 | 2017 |
| SEMGROMI—a semantic grouping algorithm to identifying microservices using semantic similarity of user stories FH Vera-Rivera, EGP Cuadros, B Perez, H Astudillo, C Gaona PeerJ Computer Science 9, e1380, 2023 | 2 | 2023 |
Jose Aguilar (orcid.org/0000-0003-41...Universidad de Los Andes (ULA).在 ula.ve 的电子邮件经过验证
