| State of the art of artificial intelligence and predictive analytics in the E&P industry: a technology survey C Bravo, L Saputelli, F Rivas, AG Pérez, M Nikolaou, G Zangl, ... Spe Journal 19 (04), 547-563, 2014 | 125 | 2014 |
| Control de sistemas no lineales: Linealización aproximada, extendida, exacta H Sira-Ramírez, R Márquez, F Rivas-Echeverría, O Llanes-Santiago Pearson Prentice Hall, 2005 | 105 | 2005 |
| Heath monitoring of capacitors and supercapacitors using the neo-fuzzy neural approach A Soualhi, M Makdessi, R German, FR Echeverría, H Razik, A Sari, ... IEEE Transactions on Industrial Informatics 14 (1), 24-34, 2017 | 84 | 2017 |
| Computación Inteligente J Aguilar, F Rivas MERITEC, June, 2001 | 71 | 2001 |
| Assessing the effectiveness of YOLO architectures for smoke and wildfire detection E Casas, L Ramos, E Bendek, F Rivas-Echeverría IEEE Access, 2023 | 58 | 2023 |
| A multiagent model for intelligent distributed control systems J Aguilar, M Cerrada, G Mousalli, F Rivas, F Hidrobo Knowledge-Based Intelligent Information and Engineering Systems: 9th …, 2005 | 53 | 2005 |
| Classification of Venezuelan spirituous beverages by means of discriminant analysis and artificial neural networks based on their Zn, Cu and Fe concentrations EA Hernández-Caraballo, RM Avila-Gómez, T Capote, F Rivas, AG Pérez Talanta 60 (6), 1259-1267, 2003 | 49 | 2003 |
| Machine learning models for the prediction of the SEIRD variables for the COVID-19 pandemic based on a deep dependence analysis of variables Y Quintero, D Ardila, E Camargo, F Rivas, J Aguilar Computers in biology and medicine 134, 104500, 2021 | 34 | 2021 |
| Evaluation of chemometric techniques and artificial neural networks for cancer screening using Cu, Fe, Se and Zn concentrations in blood serum EA Hernández-Caraballo, F Rivas, AG Pérez, LM Marcó-Parra Analytica Chimica Acta 533 (2), 161-168, 2005 | 32 | 2005 |
| Control de procesos O Camacho, A Rosales, F Rivas Quito-Ecuador: EPN Editorial, 2020 | 30 | 2020 |
| Control de sistemas no lineales H Sira, R Márquez, F Rivas, O Llanes Mdrid: Pearson Prentice Hall, 2005 | 29 | 2005 |
| Diseño de una arquitectura de automatización industrial basada en sistemas multi-agentes C Bravo, JL Aguilar, FI Rivas Ciencia e Ingeniería 25 (2), 75-88, 2004 | 29 | 2004 |
| Long-term prediction of bearing condition by the neo-fuzzy neuron A Soualhi, G Clerc, H Razik, F Rivas 2013 9th IEEE International Symposium on Diagnostics for Electric Machines …, 2013 | 25 | 2013 |
| Perfiles metabólicos en preparto, parto y postparto en vacas de raza rubia gallega: estudio preliminar LA Quintela, JJ Becerra, C Rey, C Díaz, J Cainzos, F Rivas, W Huanca, ... Recursos Rurais, 2011 | 24 | 2011 |
| Time Series Forecasting using ARIMA, Neural Networks and Neo Fuzzy Neurons J COLLANTES-DUARTE, F RIVAS-ECHEVERRÍA 3rd WSEAS International Conference on Neural Networks and Applications (NNA …, 2002 | 24 | 2002 |
| Diseño de un medio de gestión de servicios para sistemas multiagentes V Bravo, J Aguilar, F Rivas, M Cerrada Proceeding of XXX Conferencia Latinoamericana de Informática, 431-439, 2004 | 22 | 2004 |
| Sistema Inteligente para la Generación Automática de Contratos en el marco de la Ley de Contrataciones Públicas F Rivas, M Asprino, J Sarache, F León Revista Politécnica 44 (1), 41-48, 2019 | 20 | 2019 |
| Applying analytics to production workflows: Transforming integrated operations into intelligent operations C Bravo, J Rodriguez, L Saputelli, F Rivas SPE Intelligent Energy International Conference and Exhibition, SPE-167823-MS, 2014 | 20 | 2014 |
| An implementation of a distributed artificial intelligence architecture to the integrated production management C Bravo, JA Castro, L Saputelli, A Ríos, J Aguilar-Martin, F Rivas Journal of Natural Gas Science and Engineering 3 (6), 735-747, 2011 | 19 | 2011 |
| Neural network-based auto-tuning for PID controllers F Rivas-Echeverria, A Rios-Bolivar, J Casales-Echeverria Neural Network World 11 (3), 277-284, 2001 | 19 | 2001 |