| Time series forecasting using bayesian method: Application to cumulative rainfall CR Rivero, J Pucheta, M Herrera, V Sauchelli, S Laboret IEEE Latin America Transactions 11 (1), 359-364, 2013 | 35 | 2013 |
| Traditional vs. Machine-Learning Methods for Forecasting Sandy Shoreline Evolution Using Historic Satellite-Derived Shorelines FB Floris Calkoen,Arjen Luijendijk,Cristian Rodriguez Rivero,Etienne Kras Remote Sensing 13 (5), 934, 2021 | 30 | 2021 |
| Energy associated tuning method for short-term series forecasting by complete and incomplete datasets CR Rivero, J Pucheta, S Laboret, V Sauchelli, D Patiǹo Journal of Artificial Intelligence and Soft Computing Research 7 (1), 5-16, 2017 | 26 | 2017 |
| Very short term forecasting in global solar irradiance using linear and nonlinear models AD Orjuela-Cañón, J Hernández, CR Rivero 2017 IEEE workshop on power electronics and power quality applications …, 2017 | 22 | 2017 |
| A new approach for time series forecasting: bayesian enhanced by fractional brownian motion with application to rainfall series CR Rivero, D Patiño, J Pucheta, V Sauchelli International Journal of Advanced Computer Science and Applications 7 (3), 2016 | 19 | 2016 |
| A feed-forward neural networks-based nonlinear autoregressive model for forecasting time series JA Pucheta, CMR Rivero, MR Herrera, CA Salas, HD Patiño, BR Kuchen Computación y Sistemas 14 (4), 423-435, 2011 | 19 | 2011 |
| Rainfall forecasting using sub sampling nonparametric methods J Pucheta, CR Rivero, M Herrera, C Salas, V Sauchelli IEEE Latin America Transactions 11 (1), 646-650, 2013 | 15 | 2013 |
| Analysis of a Gaussian process and feed-forward neural networks based filter for forecasting short rainfall time series CR Rivero, J Pucheta, H Patiño, J Baumgartner, S Laboret, V Sauchelli The 2013 International Joint Conference on Neural Networks (IJCNN), 1-6, 2013 | 14 | 2013 |
| Short-series Prediction with BEMA Approach: application to short rainfall series CR Rivero, JA Pucheta, JS Baumgartner, SO Laboret, VH Sauchelli, ... IEEE Latin America Transactions 14 (8), 3892-3899, 2016 | 13 | 2016 |
| Short time series prediction: Bayesian Enhanced modified Approach with application to cumulative rainfall series CR Rivero, JA Pucheta, VH Sauchelli, HD Patiño International Journal of Innovative Computing and Applications 7 (3), 153-162, 2016 | 12 | 2016 |
| Short-term rainfall time series prediction with incomplete data CR Rivero, HD Patiño, JA Pucheta 2015 international joint conference on neural networks (IJCNN), 1-6, 2015 | 12 | 2015 |
| Long-term power consumption demand prediction: A comparison of energy associated and Bayesian modeling approach CR Rivero, V Sauchelli, HD Patiño, JA Pucheta, S Laboret 2015 Latin America Congress on Computational Intelligence (LA-CCI), 1-6, 2015 | 10 | 2015 |
| Forecasting short time series with missing data by means of energy associated to series CR Rivero, J Pucheta, S Laboret, D Patiño, V Sauchelli Applied mathematics 6 (09), 1611, 2015 | 10 | 2015 |
| A NN-based model for time series forecasting in function of energy associated of series CR Rivero, J Pucheta, J Baumgartner, M Herrera, D Patiño, B Kuchen Proceedings of the 2011 international conference on applied, numerical and …, 2011 | 10 | 2011 |
| Artificial Neural Networks and Machine Learning–ICANN 2019: Deep Learning: 28th International Conference on Artificial Neural Networks, Munich, Germany, September 17–19, 2019 … IV Tetko, V Kůrková, P Karpov, F Theis Springer Nature, 2019 | 9 | 2019 |
| Modelos no lineales de pronóstico de series temporales basados en inteligencia computacional para soporte en la toma de decisiones agrícolas C Rodríguez Rivero Universidad Nacional de Córdoba. Facultad de Ciencias Exactas, Físicas y …, 2016 | 9 | 2016 |
| Aspect-based sentiment analysis of social media data with pre-trained language models A Troya, R Gopalakrishna Pillai, DC Rodriguez Rivero, DZ Genc, ... Proceedings of the 2021 5th International Conference on Natural Language …, 2021 | 8 | 2021 |
| Noisy Chaotic time series forecast approximated by combining Reny's entropy with Energy associated to series method: application to rainfall series CR Rivero, J Pucheta, AO Canon, L Franco, YT Valdivia, P Otano, ... IEEE Latin America Transactions 15 (7), 1318-1325, 2017 | 8 | 2017 |
| Forecasting Rainfall Time Series with stochastic output approximated by neural networks Bayesian approach CR Rivero, JA Pucheta International journal of advanced computer science and applications 5 (6), 2014 | 8 | 2014 |
| Intelligent Computing Theories and Methodologies: 11th International Conference, ICIC 2015, Fuzhou, China, August 20-23, 2015, Proceedings, Part II DS Huang, KH Jo, A Hussain Springer, 2015 | 7 | 2015 |
Julián A. PuchetaProfessor of Electrical Engineering, National University of CordobaVerified email at unc.edu.ar
