传统的数据库都是以二值逻辑和精确数据为基础的,不能表示许多模糊不清的对象。目前模糊数据库技术是基于L.A.Zadeh所提出的模糊集,由于Vague集在表达模糊信息方面的能力比模糊集强,所以基于Vague集的模糊数据库具有广阔的应用前景。本文在Vague集和Vague关系基础上,提出基于Vague集的模糊结构化查询语言VSQL,它是针对于Vague关系模型的一种标准SQL扩展,可以应用于机器学习、决策分析、知识获取,以及模式匹配等方面。 Traditional databases are based on binary logic and exact data and can not represent many ambiguous objects. At present, the fuzzy database technology is based on the fuzzy sets proposed by L.A. Zadeh. Because Vague sets are more capable of expressing fuzzy information than fuzzy sets, the fuzzy database based on Vague sets has broad application prospects. Based on the relationship between Vague sets and Vague, this paper proposes a Fuzzy Structured Query Language (VSQL) based on Vague Sets, which is a standard SQL extension for Vague relational models and can be applied to machine learning, decision analysis, knowledge acquisition, and schema Matching and so on.