基于灰集的不确定性时空数据模型

不确定性处理是时空数据库面临的新问题。其研究的首要任务是对不确定时空对象进行建模,研究时空不确定性的表示和存储,进而设计离散模型实现数据库系统。提出了建立在灰集理论上的时空数据抽象模型,适合处理部分已知部分未知的不确定对象。首先给出了抽象数据类型的定义,包括建立在灰集理论上的基本数据类型,空间数据类型和时空数据类型;随后对不确定时空分析操作进行了简单的定性分析;最后给出不确定性时空查询的表达方式。

Uncertain Spatio-temporal Data Model Based on Grey Sets

The majority of spatio-temporal DBMS assume objects to be precise,but this simplification can't work in many military,navigation and environmental applications.Many forms of spatio-temporal data can't be measured exactly,and in these kinds of objects exists spatio-temporal indeterminacy.Spatio-temporal uncertainty management is a new topic for researchers on spatio-temporal databases.The current method based on Fuzzy Sets is not well applicable because it imposes strict restrictions on the objects' uncertainty.In this paper,a new abstract model of uncertain spatio-temporal objects is presented.This model is based on the Grey Sets and is more applicable for the presentation and manipulation of partial unknown spatio-temporal objects.This paper first gives the formal definition of uncertain abstract data types based on the Grey Sets,such as the definition of base types,spatial types and spatio-temporal types.Then we take a glimpse at the aspect of uncertain spatio-temporal analysis.Finally,examples of uncertain query is presented.