一种基于层次聚类的子系统划分方法研究

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H_pal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。

Approach to Subdividing Systems Based on Hierarchical Clustering

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,subsystems 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 H_pal 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.