中文摘要：

基于Pawlak粗糙集的知识归纳方法对改模方案描述的准确程度要求较高,且归纳得到的改模规则条数过多,导致改模知识的实际应用可行性较差。对于含有模糊描述特征值的改模方案,结合改模方案分层递阶表达模型,定义有关特征值的新息,构建基于模糊数据的改模方案及知识表达方法。利用基于模糊数据的改模方案结构化处理算法得到基于新息的改模方案特征决策表;抽取新息构造特征模糊相似矩阵,并引入置信水平矢量实现对特征决策表的模糊等价划分。结合特征决策表的单一/复合特征模糊等价划分提出基于模糊粗糙集的改模知识归纳方法,即基于模糊粗糙集的改模特征分层约简和改模规则生成算法,解决了从模糊描述的改模方案中归纳改模知识的问题。实例分析表明了该方法的可行性,归纳得到的改模知识具有较强的普适性。

英文摘要：

High accuracy of the description to injection mould repair schemes is required and excess inducted rules are obtained when the knowledge is inducted by Pawlak rough set,therefore,the feasibility of the conventional rough set in practical application is poor.By the combination of feature and concept hierarchy model and the definition of innovation about concept,the hierarchical representation of repair schemes and knowledge is put forward.The repair schemes can be reconstructed hierarchically by the calculation of innovation about concept which represents the fuzzy description of them and then feature decision tables are achieved.By the abstraction of innovation about concept from the feature decision tables,feature fuzzy similar matrix is constructed and the feature decision table is divided into some fuzzy equivalent subsets by introducing confidence level vector.The algorithm of feature reduction and knowledge induction based on fuzzy rough set is put forward by defining single or multiple fuzzy feature equivalence relations.A case study indicates that the feasibility of this method and the universality of the inducted knowledge are both prompted obviously.