摘要
重点讨论了空间数据不确定性的概念、模型及研究方法．建议用目标模型和场模型来分别表示两类不同的空间对象．论述了空间统计学、模糊集理论、粗集理论、遗传算法、反思模型等在数据不确定性研究中的应用，并给出了若干应用例子．
The current technologies in geographical information systems (GIS) allow us to acquire and integrate spatial information from different sources. Further development of GIS technologies is to handle not only spatial geometry information but also fuzzy and knowledge information. The concept, modeling and representation of spatial objects with uncertainties were emphatically discussed. Uncertain objects in reality include two major types, i.e. uncertainty due to imprecision and that due to randomness. Therefore the two types of spatial objects may be represented by object model and field model respectively. In order to characterize, model and represent uncertain objects, some methods of nonlinear sciences such as geostatistics, fuzzy set theory, rough set theory, genetic algorithm and inverse thought model were investigated. Finally, some practical applications were given.
出处
《中国矿业大学学报》
EI
CAS
CSCD
北大核心
2000年第1期20-24,共5页
Journal of China University of Mining & Technology
基金
国家自然科学基金!49871069
高校博士点基金!97029005
关键词
空间对象
不确定性
非线性科学
GIS
geographical information system
spatial object
uncertainty
nonlinear science
