Study On Expert Based On Fuzzy Conceptual Graph Knowledge Representation

Knowledge representation is an important issue in artificial intelligence research. It is the bottlenecks of the development of artificial intelligence and expert system application. Appropriate selection and proper use of knowledge representation will greatly improve the efficiency of artificial intelligence problem-solving.As a kind of knowledge representation method, conceptual graphs have got artificial intelligence experts' extensive attention for its simplicity, intuition and strong semantic representation ability. Because traditional conceptual graphs could not represent fuzzy knowledge, in this paper, fuzzy set is introduced into conceptual graphs on Morton's fuzzy conceptual graphs. We research the representation method and operation of improved fuzzy conceptual graphs, and then design the C-storage structure of improved fuzzy conceptual graphs.After research the representation method of fuzzy conceptual graphs, we represent production rule based on confidence with fuzzy conceptual graphs, combine representation method of fuzzy conceptual graphs and uncertain reasoning, develop production rule based on fuzzy conceptual graphs, and then research the reasoning and storage structure of production rule based on fuzzy conceptual graphs. In order to represent fuzzy uncertain knowledge of expert system, we introduce the representation method of fuzzy conceptual graphs into expert system, implement the knowledge representation and storage in knowledge base, and design the reasoning algorithm of reasoning machine.Finally, we implement an expert system example with representation method of fuzzy conceptual graphs. Compared with the expert system implemented with traditional methods, its efficiency of reasoning has been improved effectively, and achieved satisfactory results.