Production
https://prod.org.br/doi/10.1590/S0103-65132013005000066?lang=en
Production
Article

Comparação de previsões individuais e suas combinações: um estudo com séries industriais

Comparison of individual forecasts and their combinations: a study with industrial series

Martins, Vera Lucia M.; Werner, Liane

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Resumo

A necessidade de realizar previsões acuradas, oriunda do crescente aprimoramento tecnológico, tem estimulado a aplicação e comparação de diferentes técnicas de modelagem, assim como de métodos de combinação. Historicamente, pesquisadores consideram que combinar previsões originadas de diferentes técnicas melhora a sua acurácia, embora alguns estudos questionem se essa é realmente a melhor opção. Este trabalho procura verificar, para previsões industriais, se há diferença entre a acurácia das previsões individuais e a de suas combinações, por meio da modelagem de séries reais. Como técnicas de previsão individual, utilizam-se a metodologia Box-Jenkins e a modelagem RNA; para a combinação das previsões, utilizam-se os métodos da média aritmética e da variância mínima simplificado. A avaliação de desempenho das previsões é obtida por meio das medidas de acurácia MAPE, MSE e MAE. Como principal resultado, destaca-se a frequência predominante em que previsões obtidas pelo método da variância mínima apresentaram desempenho superior em relação às demais previsões.

Palavras-chave

Previsão. Acurácia. Combinação

Abstract

Technological development has increased the necessity for more accurate predictions that stimulate the application and comparison of modeling techniques and methods of combination. Historically, researchers have believed that combining forecasts from different techniques improves the forecasts, but some studies question whether combining is really the best option. This paper aims to verify whether there is a difference between the accuracy of individual forecasts and that of their combinations by modeling real industrial prediction series. The Box-Jenkins methodology and ANN modeling were used for individual forecasting, whereas the simplified minimum variance and mean arithmetic methods were used for forecast combinations. The performance of the predictions was evaluated by MAPE (Mean Absolute Percentual Error), MSE (Mean Square Error) and MAE (Mean Absolute Error). As the main result, we highlight the predominant frequency at which the predictions obtained by the minimum variance method show superior performance compared to other forecasts.

Keywords

Forecasting. Accuracy. Combining

References



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