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Julián A. Pucheta
Julián A. Pucheta
Professor of Electrical Engineering, National University of Cordoba
Verified email at unc.edu.ar - Homepage
Title
Cited by
Cited by
Year
Optimal greenhouse control of tomato-seedling crops
JA Pucheta, C Schugurensky, R Fullana, H Patiño, B Kuchen
Computers and electronics in agriculture 50 (1), 70-82, 2006
432006
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
352013
A statistically dependent approach for the monthly rainfall forecastfrom one point observations
J Pucheta, D Patino, B Kuchen
International Conference on Computer and Computing Technologies in …, 2008
302008
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
262017
A new image segmentation framework based on two-dimensional hidden Markov models
J Baumgartner, AG Flesia, J Gimenez, J Pucheta
Integrated Computer-Aided Engineering 23 (1), 1-13, 2016
232016
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
182016
A feed-forward neural networks-based nonlinear autoregressive model for forecasting time series
JA Pucheta, CM Rodríguez Rivero, MR Herrera, CA Salas, ...
Computación y Sistemas 14 (4), 423-435, 2011
182011
Optimal control based-neurocontroller to guide the crop growth under perturbations
J Pucheta, H Patiño, C Schugurensky, R Fullana, B Kuchen
Dynamics Of Continuous, Discrete And Impulsive Systems Special Volume …, 2007
172007
A new approach to segmentation of multispectral remote sensing images based on MRF
J Baumgartner, J Gimenez, M Scavuzzo, J Pucheta
IEEE Geoscience and Remote Sensing Letters 12 (8), 1720-1724, 2015
142015
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
142013
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
132013
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
122016
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
122016
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
122015
A neuro-dynamic programming-based optimal controller for tomato seedling growth in greenhouse systems
J Pucheta, H Patiño, R Fullana, C Schugurensky, B Kuchen
Neural processing letters 24, 241-260, 2006
122006
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
102015
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
102015
A new approach to image segmentation with two-dimensional hidden Markov models
J Baumgartner, AG Flesia, J Gimenez, J Pucheta
2013 BRICS Congress on Computational Intelligence and 11th Brazilian …, 2013
102013
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
102011
Neural Networks-Based Time Series Prediction Using Long and Short Term Dependence in the Learning Process
J Pucheta, HD Patiño, B Kuchen
proc. of the 2007 International Symposium on Forecasting, New York, USA, 57, 2007
92007
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Articles 1–20