https://scholars.lib.ntu.edu.tw/handle/123456789/612370
標題: | Color trend forecasting of fashionable products with very few historical data | 作者: | TSAN MING CHOI Hui C.-L. Ng S.-F. Yu Y. |
關鍵字: | Artificial neural network (ANN); fashion color trend forecasting; grey model (GM); intelligent systems; Markov regime switching (MS) grey | 公開日期: | 2012 | 卷: | 42 | 期: | 6 | 起(迄)頁: | 1003-1010 | 來源出版物: | IEEE Transactions on Systems, Man and Cybernetics Part C: Applications and Reviews | 摘要: | In time-series forecasting, statistical methods and various newly emerged models, such as artificial neural network (ANN) and grey model (GM), are often used. No matter which forecasting method one would apply, it is always a huge challenge to make a sound forecasting decision under the condition of having very few historical data. Unfortunately, in fashion color trend forecasting, the availability of data is always very limited owing to the short selling season and life of products. This motivates us to examine different forecasting models for their performances in predicting color trend of fashionable product under the condition of having very few data. By employing real sales data from a fashion company, we examine various forecasting models, namely ANN, GM, Markov regime switching, and GMANN hybrid models, in the domain of color trend forecasting with a limited amount of historical data. Comparisons are made among these models. Insights on the appropriate choice of forecasting models are generated. ? 2012 IEEE. |
URI: | https://www.scopus.com/inward/record.uri?eid=2-s2.0-84867858543&doi=10.1109%2fTSMCC.2011.2176725&partnerID=40&md5=9e3de2cc61248c5478a92139483dd1b5 https://scholars.lib.ntu.edu.tw/handle/123456789/612370 |
DOI: | 10.1109/TSMCC.2011.2176725 | SDG/關鍵字: | Fashion companies; Fashionable products; Forecasting methods; Forecasting models; Grey models; Historical data; Hybrid model; Real sales data; Regime switching; Time series forecasting; Trend forecasting; Color; Forecasting; Intelligent systems; Neural networks; Time series analysis |
顯示於: | 工商管理學系 |
在 IR 系統中的文件,除了特別指名其著作權條款之外,均受到著作權保護,並且保留所有的權利。