摘要
为合理确定批量定制服装的版型数量,运用K-means算法,以4个测量项目(身高、胸围、腰围、领围)为分类变量对347名男性进行聚类分析.分别以国标和非国标号型对初始聚心选择和聚类数的确定进行探讨,并以Calinski-Harabasz(CH)指标、变异系数和相对偏差比较了国标和非国标号型的聚类效果.研究结果表明,运用最大最小距离法确定初始聚心的非国标号型分类结果与国标GB/T 1335.1—2008分类结果对比,在相同CH值时,服装版型数由26减少到18,身高、胸围、领围和腰围相对偏差超过3%的比例分别从5.48%,39.48%,7.49%,60.52%降低到0.58%,8.07%,3.17%,12.97%.测量项目波动性从大到小依次为腰围、领围、胸围和身高.
In order to determine reasonable pattern number of mass customization clothing, the 347-male body data was analyzed based on K-means clustering algorithm with four classified variables such as height （H）, bust circumference （BC）, waist circumference （WC） and collar circumference （CC）. Classification methods of the non-national standard shape and national standard shape to research selection of initial centers and determination of the optimal clusters, and evaluated the cluster in Calinski-Harabasz（CH） index, coefficient of variation and relative deviation. The results show that the clothing pattern number of 26 reduces to 18 and relative deviation（H, BC, CC, WC） is decreased from 5.48%, 39.48%, 7.49%, 60.52% to 0.58%, 8.07%, 3.17%, 12.97%, when the CH index is same and compared to the non-national standard shape that maximum-minimum distance algorithm is adopted to determine the initial centers with national GB/T 1335.1--2008. The volatility of measuring items from big to small is WC, CC, BC and H.
作者
王旭
齐雪良
袁惠芬
刘新华
WANG Xu QI Xueliang YUAN Huifen LIU Xinhu(Anhui Provincial Key Laboratory of Textile Fabric The Science and Technology Public Service Platform for Textile Industry, Anhui Polytechnic University, Wuhu 241000, China)
出处
《东华大学学报（自然科学版）》
CSCD
北大核心
2017年第3期364-369,共6页
Journal of Donghua University(Natural Science)
基金
纺织面料安徽省高校重点实验室开放基金资助项目(2015FZ001)
安徽工程大学研究生实践与创新资助项目(2015)
关键词
K-MEANS算法
批量定制
号型分类
聚类分析
K-means algorithm
mass customization
shape classification
clustering analysis
