https://scholars.lib.ntu.edu.tw/handle/123456789/612383
標題: | An intelligent fast sales forecasting model for fashion products | 作者: | Yu Y. TSAN MING CHOI Hui C.-L. |
關鍵字: | Artificial neural network; Extreme learning machine; Sales forecasting | 公開日期: | 2011 | 卷: | 38 | 期: | 6 | 起(迄)頁: | 7373-7379 | 來源出版物: | Expert Systems with Applications | 摘要: | Sales forecasting is crucial in fashion business because of all the uncertainty associated with demand and supply. Many models for forecasting fashion products are proposed in the literature over the past few decades. With the emergence of artificial intelligence models, artificial neural networks (ANN) are widely used in forecasting. ANN models have been revealed to be more efficient and effective than many traditional statistical forecasting models. Despite the reported advantages, it is relatively more time-consuming for ANN to perform forecasting. In the fashion industry, sales forecasting is challenging because there are so many product varieties (i.e.; SKUs) and prompt forecasting result is needed. As a result, the existing ANN models would become inadequate. In this paper, a new model which employs both the extreme learning machine (ELM) and the traditional statistical methods is proposed. Experiments with real data sets are conducted. A comparison with other traditional methods has shown that this ELM fast forecasting (ELM-FF) model is quick and effective. ? 2010 Elsevier Ltd. All rights reserved. |
URI: | https://www.scopus.com/inward/record.uri?eid=2-s2.0-79951578472&doi=10.1016%2fj.eswa.2010.12.089&partnerID=40&md5=183c554565f1352dd69f1b7f746dce40 https://scholars.lib.ntu.edu.tw/handle/123456789/612383 |
DOI: | 10.1016/j.eswa.2010.12.089 | SDG/關鍵字: | Artificial Neural Network; Demand and supply; Extreme learning machine; Fashion industry; New model; Product variety; Real data sets; Sales forecasting; Statistical forecasting; Learning systems; Neural networks; Sales; Forecasting |
顯示於: | 工商管理學系 |
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