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分布式知识库系统中的不确定性处理
UNCERTAINTY PROCESSING IN DISTRIBUTED KNOWLEDGE-BASED SYSTEM
【摘要】 在许多情况下,知识源不可能给出确定的假设,它仅能给出假设的信任值(Belief Value)和不信任值(Disbc-lief Value).我们讨论了一种处理这种不确定性的方法,不信任值在这种方法中起着重要的作用,各个专家互相影响,通过改变自己对假设的可信度值(Certainty Facfor Value)CFV来进行合作.一个假设可信度值CFV的最终值是根据各可信度值的平均值和模糊熵来确定的.
【Abstract】 In many cases, KS (Knowledge Source) may not give definite hypothesis other than belief and disbe-lief value for hypothesis. A method of processing this uncertainty is discussed, in which disbelief value plays an im-portant part. Experts influnce each other and cooperate by modifying their CFV (Certainty Factor Value) for hy-pothesis. The final CFV for hypothesis is given based on mean and fuzzy entropy of all CFV.
【关键词】 分布式知识库系统;
不确定性处理;
平均值;
模糊熵;
【Key words】 distributed knowlodge-based system / uncertainty processing / mean / fuzzy entropy;
【Key words】 distributed knowlodge-based system / uncertainty processing / mean / fuzzy entropy;
- 【文献出处】 计算机工程 ,Computer Engineering , 编辑部邮箱 ,1993年01期
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