Time-Constrained Fashion Sales Forecasting by Extended Random Vector Functional Link Model

View Sample PDF

Author(s): Yong Yu (The Hong Kong Polytechnic University, Hong Kong), Tsan-Ming Choi (The Hong Kong Polytechnic University, Hong Kong)and Chi-Leung Hui (The Hong Kong Polytechnic University, Hong Kong)
Copyright: 2012
Pages: 7
Source title: Fashion Supply Chain Management: Industry and Business Analysis
Source Author(s)/Editor(s): Tsan-Ming Choi (The Hong Kong Polytechnic University, Hong Kong)
DOI: 10.4018/978-1-60960-756-2.ch010

Keywords: Business & Management / Business Science Reference / Operations and Service Management / Supply Chain Management

Purchase

View Time-Constrained Fashion Sales Forecasting by Extended Random Vector Functional Link Model on the publisher's website for pricing and purchasing information.

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.

The IRMA Community

Research IRM

Time-Constrained Fashion Sales Forecasting by Extended Random Vector Functional Link Model

Purchase

Abstract

Related Content

IRMA Sponsors