Abstract: In the process of achieving decision by intelligent method,in order to improve accuracy and reliability in using fuzzy rules,this paper defines the C-E model as the basis,bringing in the semantic restriction function to describe the fuzzy rules tendency.By quantitatively transformating for expert opinions,initializiting semantic restriction function for fitting rules,it raises an error-correction method that can correct errors of semantic restriction function.In the process of matching rules,it builds the fuzzy rules that can be self-adjusted.To use the design idea of frame expression method for reference,the design thought of the frame-fuzzy rules group is adopted,and the design that based on the fuzzy rule structure with semantic restriction is accomplished.A more scientific set of calculation method for the structure coincidence is brought out.On this account,to excavate experts’ depth cognition and the potential experience,lower the impact of specialized knowledge,improve the refined fuzzy sets computation.In combination with certain oilfield,utilizing the structure to accomplish the expert knowledge design about the diagnose for the broken-down wells.

Key words: C-E model, fuzzy rule, tendency degree, semantic restriction, self-adaption

摘要： 在利用智能化方法实现辅助决策的过程中,为提高模糊规则在使用中的准确度和可靠性,定义C-E模型,引入语义限制函数描述模糊规则的倾向程度。通过对专家意见的量化转换,初始化拟合规则的语义限制函数,并提出一种误差校正方法,在规则匹配过程中校正语义限制函数误差,进而构建可自适应调整的模糊规则。借鉴框架表达法的设计思想,采用框架-模糊规则组的设计思路,完成基于语义限制的模糊规则结构的设计,为该结构的吻合度计算提出一套较为科学的计算方法,以此达到挖掘专家的深度认知和潜在经验、降低专业知识影响、提高模糊集下精细化计算的目的。某采油厂的应用实例表明,利用基于语义限制的模糊规则结构可有效地实现对于故障井诊断的专家知识设计。

关键词: C-E模型, 模糊规则, 倾向程度, 语义限制, 自适应

CLC Number: 

• TP312