Title: Prediction of sales volume based on the RFID data collected from apparel shops

Authors: Shigeaki Sakurai

Addresses: Advanced IT Laboratory, Toshiba Solutions Corporation, Tokyo 183-8512, Japan

Abstract: This paper proposes a new method that efficiently uses the RFID data collected from apparel shops. This method learns prediction models from the data by using data mining techniques. The models represent relationships between the number of sales in the next term and the actions of customers, such as the number of pick-up, the number of fitting, the number of customers, and so on. It is possible to predict sales volume by applying the present RFID data to the models. Also, this paper proposes two step-wise methods in order to acquire the models. It verifies the efficiency of the method through numerical experiments based on the RFID data collected from two branches of an apparel company.

Keywords: radio frequency identification; RFID; apparel industry; support vector machines; SVM; sales volume prediction; two step-wise method; clothing industry; garment industry; prediction models; data mining.

DOI: 10.1504/IJSSC.2011.040343

International Journal of Space-Based and Situated Computing, 2011 Vol.1 No.2/3, pp.174 - 182

Published online: 26 Mar 2015 *

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