摘要
针对高端制造业客户需求数据庞大、需求间相关关系复杂的问题,提出了基于加权网络的客户需求聚类方法。将客户需求看做加权网络的节点,将客户需求之间的相关关系看做加权网络的边,构建客户需求的加权网络,并在加权网络的基础上结合聚类算法对客户需求进行聚类处理,从而将杂乱无章的客户需求根据相关程度进行分类。考虑到需求之间关系的主观性和模糊性,采用三角模糊数来量化加权网络的边权,最后以客户对塔式起重机的需求为例对所提方法的有效性进行了验证。
In order to solve the problem of large customer requirements(CR)data and complex requirement correlation in high-end manufacturing industry,this paper proposed a clustering method of CR based on weighted network.This method regarded CR as the node of weighted network,regarded the correlation between CR as the edge of the weighted network,constructed the weighted network of CR,and clustered CR on the basis of weighted network with clustering algorithm,thus classified the disordered CR according to the degree of correlation.Considering the subjectivity and fuzziness of the relationship between requirements,this paper used a triangular fuzzy number to quantify the edge weights of the weighted network.Finally,this paper verified the effectiveness of the proposed method by taking the customer’s requirement for tower cranes as an example.
作者
耿秀丽
樊志娟
Geng Xiuli;Fan Zhijuan(Business School,University of Shanghai for Science&Technology,Shanghai 200093,China)
出处
《计算机应用研究》
CSCD
北大核心
2020年第10期2941-2944,2950,共5页
Application Research of Computers
基金
国家自然科学基金资助项目(71301104)
国家教育部人文社会科学研究规划基金资助项目(19YJA630021)
高等学校博士学科点专项科研基金资助项目(20133120120002)。
关键词
加权网络
客户需求
聚类算法
三角模糊数
weighted network
customer requirements
clustering algorithm
triangular fuzzy number