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Combination of Box-Jenkins and MLP/RNA models for forecasting

Jacobs, W. ; Souza, A. M. ; Zanini, R. R.

Revista IEEE América Latina, 2016-04, Vol.14 (4), p.1870-1878

Los Alamitos: IEEE

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Título:
Combination of Box-Jenkins and MLP/RNA models for forecasting
Autor: Jacobs, W. ; Souza, A. M. ; Zanini, R. R.
Assuntos: ARIMA Model ; Artificial Neural Network ; Artificial neural networks ; Dairy industry ; Demand Forecast ; Economic forecasting ; Forecast Combination ; Inverse ; Jacobian matrices ; Mathematical model ; Mathematical models ; Mean square values ; Multilayer Perceptron ; Predictive models ; Production planning ; Reactive power ; Ribonucleic acids ; RNA ; Root mean square ; Time series
É parte de: Revista IEEE América Latina, 2016-04, Vol.14 (4), p.1870-1878
Notas: ObjectType-Article-1
SourceType-Scholarly Journals-1
ObjectType-Feature-2
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Descrição: This study aims to predict the values of the time series of UHT milk demand in a dairy industry by combining forecasting of ARIMA and MLP/RNA models and compare the results to the individual models, exemplifying the combined forecast for the production planning. Eight predictions combining techniques were used and, after the use of statistical techniques, the results obtained by fitting the ARIMA and MLP/RNA templates were compared with the results obtained in the proposed combinations. The results showed that the combination of SARIMA models (3,0,1)(1,1,0)12 and DMLP the inverse mean square method provided a performance in the forecast, for six months ahead, 66.5% higher than the individual models where the combination of forecasts provided a RMSE of 1.43 and MAPE of 2.16. The forecast for 12 months on, the performance of the combination was 56.5% higher compared to individual models, with RMSE of 2.86 and MAPE of 3.70%. In both cases, the combination of predictions showed superior results.
Editor: Los Alamitos: IEEE
Idioma: Inglês

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Combination of Box-Jenkins and MLP/RNA models for forecasting

Jacobs, W. ; Souza, A. M. ; Zanini, R. R.

Los Alamitos: IEEE

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