Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/65025
Title: Time-constrained fashion sales forecasting by extended random vector functional link model
Authors: Yu, Y
Choi, TM 
Hui, CL 
Issue Date: 2012
Publisher: Business Science Reference/IGI Global
Source: In TM Choi (Ed.), Fashion supply chain management : industry and business analysis, p. 185-191. Hershey, Pa.: Business Science Reference/IGI Global, 2012 How to cite?
Abstract: Forecasting is about providing estimation of the future that cannot be observed at the moment. In this chapter, the random vector functional link (RVFL), which is a variation of the artificial neural networks (ANN) model, is used in establishing a fashion sales forecasting model. It is well-known that the RVFL inherits the learning and approximation capability of ANN, while running much faster than the traditional ANN. In order to develop a real world forecasting application, we propose a time-constrained forecasting model (TCFM), implemented by an extended RVFL, in which the user can define the time limit and a precision threshold for yielding the forecasting result. Real datasets collected from a fashion retail company are employed for the analysis. Our experiment has shown that the proposed TCFM can produce quality forecasting within the given time constraint. Future research directions are outlined.
URI: http://hdl.handle.net/10397/65025
ISBN: 9781609607579 (electronic bk.)
9781609607562
9781609607586
DOI: 10.4018/978-1-60960-756-2.ch010
Appears in Collections:Book Chapter

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