Research on Knowledge Hierarchical Induction for Injection Mould Repairs based on Rough Set

摘要

By the combination of feature and concept hierarchy model and the definition of innovation about concept, the method of structured processing and knowledge hierarchical representation for injection mould repair schemes is put forward under the condition of non-fuzzy or fuzzy data. Rule sets can be provided by knowledge induction for injection mould repairs based on basic rough set, but the rule sets are large-scale and the applicability is poor in practice. Aiming at achieving the rule sets more efficiently and applicably, a new method of knowledge hierarchical induction based on variable precision rough set is proposed. For injection mould repair schemes based on fuzzy data, 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. Finally, the algorithm of feature reduction and knowledge induction based on fuzzy rough set is put forward by defining single or multi-fuzzy feature equivalence relations. The feasibility and effectiveness of two methods for knowledge hierarchical induction under different data environments are both analyzed.