基于粗糙集理论的计算机图像识别系统

Expert Diagnosis System Based on Rough Set Theory

为解决专家系统较难获取完备知识的瓶颈问题,设计了一种基于粗糙集理论的诊断系统。研究历史数据所形成的决策表,运用粗糙集理论进行约简,构建专家系统知识库模型。通过计算诊断规则粗糙度,确定诊断规则的置信程度。利用推理机,实现对知识库的动态维护。结合诊断的特点,建立基于粗糙集理论的专家诊断系统模型,快速准确地实现诊断的目标。实例表明,该专家诊断系统有效、实用,具有很好的学习能力。

In order to resolve the bottleneck problem of obtaining complete knowledge of expert system,a new expert system based on the Rough Set is proposed. Form the decision table defined by history pathology data,the paper applies the reduction of decision table in rough sot theory ,builds the knowledge base model. The belief degree of diagnosis rules is determined by calculating the rough subjection degree of every rule. The knowledge base is maintained through reasoning. Combining with the characteristic of diagnosis, expert diagnosis system model based on Rough Set was established and it actualize the aim of diagnosis. It is proved that the expert diagnosis system is effective and applied. It also has good ability of containing error and study.