基于改进FKCM方法的针织纱质量评价  

Quality evaluation of knitting yarns using modified FKCM

作　　者：刘皓[1] 成玲[1] 

机构地区：[1]天津工业大学纺织学院,天津300160

出　　处：《纺织学报》2009年第1期37-41,共5页Journal of Textile Research

摘　　要：为对针织纱线的质量进行更客观准确的评价,提出应用改进的模糊核C-均值(FKCM)聚类算法对针织纱测量数据集聚类,改进FKCM聚类方法,将低维输入空间数据通过核函数映射到高维的特征空间,然后在特征空间应用FCM聚类分析对数据进行聚类分析,构造了核F(KF)统计量寻找合理的聚类数,最后建立聚类类别和质量等级之间的对应关系模型。通过对IRIS数据分析,显示应用改进的FKCM具有较好的分类效果,将这种方法应用到实测数据,KF指标显示样本分2类是较合理的。依据建立的类别质量等级函数即可确定每类样本的质量等级。改进的FKCM方法和KF指标结合能够有效地对多指标数据集进行分析。In order to evaluate more objectively the performance of knitting yarns, a method using modified fuzzy kernel C-Means （FKCM） clustering algorithm for processing and analyzing dataset of knitting yarns is proposed, in which, the data of low dimension input space is mapped to high dimension feature space, FCM clustering algorithm is performed in the feature space, then the kernel F clustering validity index is designed for seeking the fitness clustering number, and the corresponding relationship model of class sequence numbers and quality grades is constructed. By analyzing the IRIS Dataset, the result shows the modified FKCM has obtained better classification effect. When it is applied to measuring dataset, and KF index indicates it is reasonable to classify the samples into two kinds. According to the constructed relation of classes and quality grades, the quality grade of each class is acquired. The combination of modified FKCM and KF index provides an efficient data analysis method for multi-index dataset.

关 键 词：针织纱 质量评价 模糊核C-均值 核方法 聚类 

分 类 号：TS101.922[轻工技术与工程—纺织工程] TS101.11[轻工技术与工程—纺织科学与工程]