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Analysis of a Gaussian process and feed-forward neural networks based filter for forecasting short rainfall time series.

C. Rivero, J. Pucheta, H. Patiño, J. Baumgartner, S. Laboret, and V. Sauchelli. IJCNN, page 1-6. IEEE, (2013)

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Julián Pacho

Julián Gallego Llerena

Julián Blanco Rodríguez

Julián Aranda Martínez

Julian Gonska

Mikromechanische Biegebalken als hochsensitive SensorenJ. Gonska. Uni Freiburg, (2009)

Other publications of authors with the same name

Fisher Vectors for Leaf Image Classification: An Experimental Evaluation.J. Redolfi, J. Sánchez, and J. Pucheta. CIARP, volume 9423 of Lecture Notes in Computer Science, page 298-305. Springer, (2015)An Approach for Time Series Forecasting by Simulating Stochastic Processes Through Time Lagged Feed-forward Neural Network.C. Rivero, J. Pucheta, J. Baumgartner, H. Patiño, and B. Kuchen. DMIN, page 287-293. CSREA Press, (2010)Short-Term Rainfall Forecasting with E-LSTM Recurrent Neural Networks Using Small Datasets.C. Rivero, J. Pucheta, H. Patiño, P. Otaño, L. Franco, and G. Juárez. ICIC (3), volume 12465 of Lecture Notes in Computer Science, page 258-270. Springer, (2020)Neuro-dynamic programming-based optimal control for crop growth in precision agriculture.H. Patiño, J. Pucheta, R. Fullana, C. Schugurensky, and B. Kuchen. ISIC, page 397-402. IEEE, (2004)Time-series prediction with BEMCA approach: Application to short rainfall series.C. Rivero, Y. Túpac, J. Pucheta, G. Juárez, L. Franco, and P. Otaño. LA-CCI, page 1-6. IEEE, (2017)Analysis of a Gaussian process and feed-forward neural networks based filter for forecasting short rainfall time series.C. Rivero, J. Pucheta, H. Patiño, J. Baumgartner, S. Laboret, and V. Sauchelli. IJCNN, page 1-6. IEEE, (2013)Dynamic model change analysis of social behavior processes during the COVID19 pandemic.J. Pucheta, S. Laboret, H. Patiño, C. Salas, C. Rivero, and M. Herrera. CSCI, page 1381-1387. IEEE, (2021)Spatial and temporal analysis of the Monte Buey SAOCOM and SMAP core site.M. Thibeault, J. Caceres, D. Dadamia, A. Soldano, M. Quirno, J. Guerrieri, R. Edrosa, M. Palomeque, L. Romaldi, J. Pucheta and 6 other author(s). IGARSS, page 969-971. IEEE, (2015)Noisy chaotic time series forecast approximated by combining Reny's entropy with energy associated to series method: Application to rainfall series.C. Rivero, J. Pucheta, S. Laboret, V. Sauchelli, A. Orjuela-Cañón, and L. Franco. LA-CCI, page 1-6. IEEE, (2016)A Statistically Dependent Approach for the Monthly Rainfall Forecastfrom One Point Observations.J. Pucheta, H. Patiño, and B. Kuchen. CCTA (2), volume 294 of IFIP Advances in Information and Communication Technology, page 787-798. Springer, (2008)

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Disambiguation of "Pucheta, Julián A."

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Analysis of a Gaussian process and feed-forward neural networks based filter for forecasting short rainfall time series.

Please choose a person to relate this publication to

Julián Pacho

Julián Gallego Llerena

Julián Blanco Rodríguez

Julián Aranda Martínez

Julian Gonska

Other publications of authors with the same name

Disambiguation

BibSonomy

Disambiguation of "Pucheta, Julián A."

copydeleteadd this publication to your clipboardcommunity posthistory of this postURLDOIBibTeXEndNoteAPAChicagoDIN 1505HarvardMSOffice XML Analysis of a Gaussian process and feed-forward neural networks based filter for forecasting short rainfall time series.

Please choose a person to relate this publication to

Julián Pacho

Julián Gallego Llerena

Julián Blanco Rodríguez

Julián Aranda Martínez

Julian Gonska

Other publications of authors with the same name

Disambiguation

copy delete add this publication to your clipboard
community post
history of this post
URL
DOI
BibTeX
EndNote
APA
Chicago
DIN 1505
Harvard
MSOffice XML

Analysis of a Gaussian process and feed-forward neural networks based filter for forecasting short rainfall time series.