Demand Forecasting by the Neural Network with Discrete Fourier Transform

Authors:
Mariko Yohda;Makiko Saito-Arita;Akira Okada;Ryota Suzuki;Yoshitsugu Kakemoto
Affiliations:
-;-;-;-;-
Venue:
ICDM '02 Proceedings of the 2002 IEEE International Conference on Data Mining
Year:
2002

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Abstract

This paper proposes a new demand forecastingmethod using the Neural Network and Fourier Transform.In this method, time series data of sales resultsconsidered as a combination of frequency aretransformed into several frequency data. They areidentified from objective indexes that consist of productproperties or economic indicators and so forth. Thismethod is efficient for demand forecasting aimed at newproducts that have no historical data.