Time-series Prediction with BEMCA Approach: application to short rainfall series
Fil: Rodriguez Rivero, Cristian. Universidad Nacional de Córdoba. Facultad de Ciencias Exactas, Físicas y Naturales. Departamento de Ingeniería Electrónica; Argentina.
| Main Authors: | , , , , , |
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| Format: | conferenceObject |
| Language: | eng |
| Published: |
2025
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| Subjects: | |
| Online Access: | http://hdl.handle.net/11086/557243 |
| _version_ | 1841742276766728192 |
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| author | Rodríguez Rivero, Cristian Tupac, Yvan Pucheta, Julian Juarez, Gustavo Franco, Leonardo Otaño, Paula |
| author_facet | Rodríguez Rivero, Cristian Tupac, Yvan Pucheta, Julian Juarez, Gustavo Franco, Leonardo Otaño, Paula |
| author_sort | Rodríguez Rivero, Cristian |
| collection | Repositorio Digital Universitario |
| description | Fil: Rodriguez Rivero, Cristian. Universidad Nacional de Córdoba. Facultad de Ciencias Exactas, Físicas y Naturales. Departamento de Ingeniería Electrónica; Argentina. |
| format | conferenceObject |
| id | rdu-unc.557243 |
| institution | Universidad Nacional de Cordoba |
| language | eng |
| publishDate | 2025 |
| record_format | dspace |
| spelling | rdu-unc.5572432025-08-27T12:21:10Z Time-series Prediction with BEMCA Approach: application to short rainfall series Rodríguez Rivero, Cristian Tupac, Yvan Pucheta, Julian Juarez, Gustavo Franco, Leonardo Otaño, Paula Forecasting Relative entropy Permutation entropy Ingeniería electrónica Inteligencia Artificial Fil: Rodriguez Rivero, Cristian. Universidad Nacional de Córdoba. Facultad de Ciencias Exactas, Físicas y Naturales. Departamento de Ingeniería Electrónica; Argentina. Fil: Tupac, Yvan. Universidad Catolica San Pablo. Departamento de Ciencias de la Computación; Brasil. Fil: Pucheta, Julian Antonio. Universidad Nacional de Córdoba. Facultad de Ciencias Exactas, Físicas y Naturales. Departamento de Ingeniería Electrónica; Argentina. Fil: Juarez, Gustavo. Universidad Nacional de Tucumán. Laboratorio de Inteligencia Artificial; Argentina. Fil: Franco, Leonardo. Universidad de Málaga. Departamento de Ciencias de la Computación; España. Fil: Otaño, Paula. Universidad Tecnológica Nacional. Departamento de Ingeniería en Sistemas; Argentina. This paper presents a new method to forecast short rainfall time-series. The new framework is by means of Bayesian enhanced modified combined approach (BEMCA) using permutation and relative entropy with Bayesian inference. The aim at the proposed filter is focused on short datasets consisting of at least 36 samples. The structure of the artificial neural networks (ANNs) change according to data model selected, such as the Bayesian approach can be combined with the entropic information of the series. Then computational results are assessed on time series competition and rainfall series, afterwards they are compared with ANN nonlinear approaches proposed in recent work and naïve linear technique such us ARMA. To show a better performance of BEMCA filter, results are analyzed in their forecast horizons by SMAPE and RMSE indices. BEMCA filter shows an increase of accuracy in 3-6 prediction horizon analyzing the dynamic behavior of chaotic series for short series predictions. Fil: Rodriguez Rivero, Cristian. Universidad Nacional de Córdoba. Facultad de Ciencias Exactas, Físicas y Naturales. Departamento de Ingeniería Electrónica; Argentina. Fil: Tupac, Yvan. Universidad Catolica San Pablo. Departamento de Ciencias de la Computación; Brasil. Fil: Pucheta, Julian Antonio. Universidad Nacional de Córdoba. Facultad de Ciencias Exactas, Físicas y Naturales. Departamento de Ingeniería Electrónica; Argentina. Fil: Juarez, Gustavo. Universidad Nacional de Tucumán. Laboratorio de Inteligencia Artificial; Argentina. Fil: Franco, Leonardo. Universidad de Málaga. Departamento de Ciencias de la Computación; España. Fil: Otaño, Paula. Universidad Tecnológica Nacional. Departamento de Ingeniería en Sistemas; Argentina. Sistemas de Automatización y Control 2025-08-26T13:38:12Z 2025-08-26T13:38:12Z 2017 conferenceObject http://hdl.handle.net/11086/557243 eng Attribution-NonCommercial-NoDerivatives 4.0 International http://creativecommons.org/licenses/by-nc-nd/4.0/ Impreso |
| spellingShingle | Forecasting Relative entropy Permutation entropy Ingeniería electrónica Inteligencia Artificial Rodríguez Rivero, Cristian Tupac, Yvan Pucheta, Julian Juarez, Gustavo Franco, Leonardo Otaño, Paula Time-series Prediction with BEMCA Approach: application to short rainfall series |
| title | Time-series Prediction with BEMCA Approach: application to short rainfall series |
| title_full | Time-series Prediction with BEMCA Approach: application to short rainfall series |
| title_fullStr | Time-series Prediction with BEMCA Approach: application to short rainfall series |
| title_full_unstemmed | Time-series Prediction with BEMCA Approach: application to short rainfall series |
| title_short | Time-series Prediction with BEMCA Approach: application to short rainfall series |
| title_sort | time series prediction with bemca approach application to short rainfall series |
| topic | Forecasting Relative entropy Permutation entropy Ingeniería electrónica Inteligencia Artificial |
| url | http://hdl.handle.net/11086/557243 |
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