一个基于模糊逻辑的不确定性推理模型

An Uncertainty Inference Model Based on Fuzzy Logic

针对合取运算、析取运算和加权平均运算在求解人机智能化CAPP系统的实际问题时所存在的不足,提出了以权系数为基础的广义模糊逻辑概念.在此基础上,构建了基于模糊逻辑的不确定性推理模型.通过在该模型中引入一组新的函数(即组合函数、匹配函数、传递函数和选择函数),较好地解决了推理中不确定性的匹配与传播这一关键问题,并使用Visual Prolog 5.2智能语言实现了不确定性推理的过程,从而使CAPP系统中模糊工艺知识的获取、表达与应用得以基本实现.

Acording to some shortcomings of the conjunction operation, disjunction operation and weighted average operation in solving practical problem of human-computer intellectualization CAPP system, the concept of general fuzzy logic based on weight coefficient is presented. On the basis of above work, uncertainty inference model based on fuzzy logic is constructed. A group of new functions （combination function, match function, transfer function, and choice function） in the model is introduced, the key problem of uncertainty match and transmit in inference procedure is solved better, and the process of uncertainty inference is realized by Visual Prolog 5.2 intelligent languages. Thus the acquisition, representation and application of fuzzy process knowledge in CAPP system is basically realized.