摘要
应用F-分析法对面粉厂37种不同系统粉进行聚类分析,验证了以L*值作为衡量面粉精度指标的合理性,并提出标准模型库的概念,借助格贴近度和最大隶属原则,为其他面粉加工精度的归类和识别提供了一种新的参考方法。
The rationality of L＊ value as index on measuring flour milling degree was verified through analysis of 37 kinds of system flour by fuzzy cluster method in this study. A concept of standard model database was established with the help of Lattice closeness degree and Maximum membership principle. The present study provided a new reference for the classification and recognition method of flour milling degree.
出处
《河南工业大学学报（自然科学版）》
CAS
北大核心
2016年第5期107-110,共4页
Journal of Henan University of Technology：Natural Science Edition
基金
国家自然科学基金项目(11301150)
河南省自然科学基金项目(142300410134)
关键词
面粉精度指标
模糊聚类
模糊识别
格贴近度
模型库
flour milling degree index
fuzzy cluster
fuzzy recognition
lattice closeness degree
model database
