信息系统中的熵理论和信息粒度  

Entropy Theory and Information Granularity in Information Systems

作　　者：滕书华[1] 鲁敏[1] 张军[1] 谭志国[1] 庄钊文[1] 

机构地区：[1]国防科学技术大学电子科学与工程学院,湖南长沙410073

出　　处：《计算机工程与科学》2012年第4期94-101,共8页Computer Engineering & Science

基　　金：中国博士后科学基金资助项目(20110481511);国家自然科学基金资助项目(60972114)

摘　　要：不确定性是人工智能中的研究热点,而熵理论和信息粒度是度量信息系统不确定性的两种主要方法。本文在给出信息系统中熵的物理意义基础上,提出了信息系统中熵增加原理,给出了熵和信息粒度的公理化定义,据此构造了两种新的不确定性度量函数—α熵和α粒度,它们是已有熵和粒度度量的进一步推广。研究表明,α熵以及现有的熵度量都是广义熵的特殊形式,而α粒度以及现有的粒度度量都是广义粒度的特殊形式,从而统一、规范和发展了完备与不完备信息系统中的不确定性度量方法。One of the most important issues in artificial intelligence is uncertainty.Many uncertainty measuring methods have been put forward and widely used in information systems,such as entropy theory and information granularity,which are two main approaches to study the uncertainty of an information system.In this paper,the physical meaning of entropy and the entropy increase principle in information systems are presented firstly,then the axiom definitions of entropy and information granularity are provided and two new uncertainty measureing functions α-entropy and α-granularity using this method are developed.Analysis shows that some of the existing definitions of entropy and information granularity become the special forms of axiom definitions.The results unify,standardize and develop the theory of uncertainty measureing in complete and incomplete information systems.

关 键 词：信息系统 熵 信息粒度 粗糙集 不确定性 

分 类 号：TP181[自动化与计算机技术—控制理论与控制工程]