Abstract
The fuzzy logic and expert system are important techniques to enhance the level of machine reasoning. Object-oriented techniques have been widely adopted to create expert systems. In this paper, we propose a novel object-oriented fuzzy expert system framework which constructs large-scale knowledge-based system effectively. In this method, rules and facts in the system are organized into different object groups respectively. The fact objects can keep the features of traditional object-oriented model such as the inheritance, capsulation and polymorphism. The rule objects contain several specific components to process fuzzy information and imprecise inferencing. Due to object-oriented techniques, knowledge representation and maintenance can be much more convenient than traditional expert system. We also present and prove two different inference strategies with fuzzy features under this framework. At last,a case of health evaluation expert system is discussed.
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