MODELLING AND FORECAST OF CHARCOAL PRICES USING A NEURO-FUZZY SYSTEM
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| Format: | Artículo científico |
| Langue: | en |
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Universidade Federal de Lavras
2016
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| _version_ | 1876467362400567296 |
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| author | Carlos Alberto Araújo Júnior |
| author_facet | Carlos Alberto Araújo Júnior |
| contents | MODELLING AND FORECAST OF CHARCOAL PRICES USING A NEURO-FUZZY SYSTEM Carlos Alberto Araújo Júnior Liniker Fernandes da Silva Marcio Lopes da Silva Helio Garcia Leite Erlon Barbosa Valdetaro Danilo Barros Donato Renato Vinícius Oliveira Castro Agrociencias ANFIS Time series Computational intelligence Using a monthly time series of charcoal prices in Minas Gerais from January 2000 to September 2014, this study aimed to evaluate the use of neuro-fuzzy system to model the series and forecasting prices. We used four modeling structures for different prices lags (1, 2, 3, 4 and 5 lags). The structure most appropriate for neuro-fuzzy system was chosen based on the root mean square error, mean absolute error, mean squared error, mean absolute percentage error and maximum absolute percentage error for the forecasted period. With the results found, it is possible to conclude that a neuro-fuzzy system can be used properly to predict the charcoal prices. 2016 artículo científico 0104-7760 https://www.redalyc.org/articulo.oa?id=74446629003 en http://www.redalyc.org/revista.oa?id=744 CERNE application/pdf Universidade Federal de Lavras CERNE (Brasil) Num.2 Vol.22 |
| format | Artículo científico |
| id | redalyc_74446629003 |
| institution | Redalyc |
| language | en |
| publishDate | 2016 |
| publisher | Universidade Federal de Lavras |
| spellingShingle | MODELLING AND FORECAST OF CHARCOAL PRICES USING A NEURO-FUZZY SYSTEM Carlos Alberto Araújo Júnior Agrociencias ANFIS Time series Computational intelligence MODELLING AND FORECAST OF CHARCOAL PRICES USING A NEURO-FUZZY SYSTEM Carlos Alberto Araújo Júnior Liniker Fernandes da Silva Marcio Lopes da Silva Helio Garcia Leite Erlon Barbosa Valdetaro Danilo Barros Donato Renato Vinícius Oliveira Castro Agrociencias ANFIS Time series Computational intelligence Using a monthly time series of charcoal prices in Minas Gerais from January 2000 to September 2014, this study aimed to evaluate the use of neuro-fuzzy system to model the series and forecasting prices. We used four modeling structures for different prices lags (1, 2, 3, 4 and 5 lags). The structure most appropriate for neuro-fuzzy system was chosen based on the root mean square error, mean absolute error, mean squared error, mean absolute percentage error and maximum absolute percentage error for the forecasted period. With the results found, it is possible to conclude that a neuro-fuzzy system can be used properly to predict the charcoal prices. 2016 artículo científico 0104-7760 https://www.redalyc.org/articulo.oa?id=74446629003 en http://www.redalyc.org/revista.oa?id=744 CERNE application/pdf Universidade Federal de Lavras CERNE (Brasil) Num.2 Vol.22 |
| title | MODELLING AND FORECAST OF CHARCOAL PRICES USING A NEURO-FUZZY SYSTEM |
| topic | Agrociencias ANFIS Time series Computational intelligence |
| url | https://www.redalyc.org/articulo.oa?id=74446629003 |