基于小波分析与动态GM(1,1)模型的服装流行色预测  

Fashion color prediction based on wavelet analysis and dynamic GM(1,1) model

作　　者：王明月 周捷[1] 李健[1] WANG Mingyue;ZHOU Jie;LI Jian(School of Apparel and Art Design,Xi′an Polytechnic University,Xi′an 710048,China)

机构地区：[1]西安工程大学服装与艺术设计学院

出　　处：《西安工程大学学报》2019年第5期475-480,共6页Journal of Xi’an Polytechnic University

基　　金：陕西省科技厅国际科技合作计划项目(2018KW-056)

摘　　要：为提高服装流行色的预测精度,以中国纺织信息中心发布的2010—2019年春夏流行色定案为研究对象,采用小波分析提取原始序列中的有效信息并进行优化,结合动态灰色GM(1,1)模型对服装流行色的色彩进行预测。结果表明,将小波分析与动态GM(1,1)模型结合进行服装流行色预测,克服了传统预测模型的缺陷,预测精度高,平均相对误差仅为1.63%,预测效果优于动态灰色模型和静态灰色模型,略优于小波静态灰色模型。In order to improve the prediction accuracy of the fashion color,the final report of the spring and summer 2010-2019 fashion color released by the China Textile Information Center is used as the research object,and the wavelet analysis is adopted to extract and optimize the effective information in the original sequence.The clothing fashion color prediction is made with the dynamic grey GM(1,1) model. The results show that the wavelet analysis combined with the dynamic GM(1,1) model overcomes the defects of the traditional prediction model with high prediction accuracy. The average relative error is only 1.63%. The prediction effect is better than that of dynamic grey model and static grey model,and slightly better than that of wavelet static grey model.

关 键 词：流行色预测 小波分析 灰色模型 预测精度 平均相对误差 

分 类 号：TS941.7[轻工技术与工程—服装设计与工程]