中文摘要：

为了更有效地表达语义Web中的模糊知识,将模糊概念与关系引入到传统的模型中,提出新的模糊本体：模糊领域本体与模糊顶层本体。模糊顶层本体从语言变量的形式化表示入手,考虑模糊概念间的语义关系：集合关系、序关系与等价关系。用模糊本体对智能交通领域的知识进行建模,通过模糊语言值描述交通概念的属性信息,有效克服现有模型的一些局限。结果表明,该研究有利于语义Web环境下模糊系统的知识共享与重用.

英文摘要：

In order to present the fuzzy knowledge more effectively on the Semantic Web,there is a need to introduce fuzzy concepts and relations into traditional models.In this paper,it proposes a new series of fuzzy ontology models that consist of fuzzy domain ontology and fuzzy upper ontology.Based on linguistic variables,which are the basis of fuzzy systems,the fuzzy upper ontology models introduce the semantic relationships between fuzzy concepts,including set relations,order relations and equivalence relations.The case study is to use fuzzy ontology to model knowledge of intelligent transportation.The result shows that these models can overcome the localization of other fuzzy ontology models.The study facilitates the knowledge sharing and reuse for fuzzy systems on the Semantic Web.