Research for service flow module granularity design based on fuzzy spaces quotient theory

被引:3
|
作者
Zhang, Fei [1 ]
机构
[1] China Jiliang Univ, Inst Mech Engn, Hangzhou 310027, Zhejiang, Peoples R China
来源
CLUSTER COMPUTING-THE JOURNAL OF NETWORKS SOFTWARE TOOLS AND APPLICATIONS | 2019年 / 22卷 / Suppl 3期
基金
中国国家自然科学基金;
关键词
Modular design of service flow; Fuzzy quotient space theory; Granularity computing; Process chain network; Grey evaluation; SUPPLY CHAINS;
D O I
10.1007/s10586-017-1623-8
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
In the research of modular design of service flow, this paper proposes a method to partition the service flow module based on fuzzy spaces quotient theory to reduce the subjectivity of module granularity selection. On the basis of service elements identification, the interrelation among service elements is analyzed in detail. And the further evaluation is made from three aspects such as service flow relevance, service source relevance and service function relevance. By working out similarity matrix between service elements and clustering attributes, the integrated fuzzy similarity matrix is obtained. And the service flow module granularity space is educated by cluster service elements through acquiring hierarchical structure using algorithm. Finally by the grey relational analysis theory and the proper index system, the optimal project of service flow module can be obtained. In this paper, the feasibility of the method above is verified by the maintenance service flow and the module granularity design of the excavator walking mechanism.
引用
收藏
页码:S5825 / S5837
页数:13
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