摘要
信息领域中常常会涉及到子系统的划分问题,而U/C矩阵法是信息系统划分的一种常用方法,但是系统的复杂性以及人为的参与常常导致子系统划分产生低效率、不确定性以及错误划分等问题。因此深入剖析了系统与子系统、子系统与功能、功能与数据等之间的关系与性质,通过对U/C矩阵按照功能相似度进行层次聚类,并引入结构熵和Hpal熵来对聚类形成的子系统进行度量,给出了具体的计算公式,提出了一种新的划分子系统的方法,将原本需要人为参与的事情转变为通过计算来完成。同时,实现了一个原型系统来对所提出的方法进行验证,并给出了具体实例。
System subdivision always is involved in the information technology domain,and a commonly used method is the U/C Matrix. However, the system complexity and the factor of people will cause some critical problems, such as inefficiency, uncertainty and mistakenly division. Consequently, the relationship between system and subsystems, subsys- tems and functions, functions and data, as well as properties of these relationships were discussed. The subsystem hierarchically clustered according to the simulation of functions was measured by structure entropy and Hpal entropy,and a series of computational formula were given. This new way of system subdivision changes the things finished by people to computation. Meanwhile,a prototype system was accomplished and a case study was analyzed to verify the theory.
出处
《计算机科学》
CSCD
北大核心
2015年第12期108-114,共7页
Computer Science
基金
国家自然科学基金资助项目(61379032
61262024
61262025
61462091
61462095)
云南省自然科学青年基金(2014FD006)
云南省教育厅科研重点项目(2013Z057)
云南省软件工程重点实验室开放基金(2012SE401)
云南省科技厅面上项目(2012FB119)
云南大学研究生科研课题项目(ynuy201375
ynuy201425)
云南省博士研究生学术新人奖资助
关键词
子系统划分
层次聚类
结构熵
U/C矩阵
功能相似度
System subdivision, Hierarchical clustering, Structure entropy, U/C matrix, Function similarity
