云理论及其在空间数据发掘和知识发现中的应用  

Cloud Theory and Its Applications in Spatial Data Mining and Knowledge Discovery

作　　者：邸凯昌[1] 李德毅[2] 李德仁[3] 

机构地区：[1]国土资源部航空物探遥感中心,北京100083 [2]中国电子系统工程研究所,北京100036 [3]武汉测绘科技大学信息工程学院,武汉430079

出　　处：《中国图象图形学报（A辑）》1999年第11期930-935,共6页Journal of Image and Graphics

基　　金：国家自然科学基金及;绘遥感信息工程国家重点实验室基金

摘　　要：云理论是以研究定性定量间的不确定性转换为基础的系统处理不确定性问题的一种新理论，包括云模型、虚云、云运算、云变换、不确定性推理等内容。云理论为数据发掘和知识发现中的许多基础性关键问题提供了新的解决方法，如概念和知识表达、定性定量转换、概念的综合与分解、从数据中生成概念和概念层次结构等。云模型是定性定量间的不确定性转换模型，它用期望值Ｅｘ、熵Ｅｎ 和超熵Ｈｅ表征定性概念，将概念的模糊性和随机性集成在一起。该文介绍了云理论的基本原理和方法及其在空间数据发掘和知识发现中的应用。Cloud theory is a new theory handling uncertainty based on the uncertain transition between qualitatives and quantitatives. The theory includes cloud model, virtual cloud, cloud operation, cloud transform and uncertainty reasoning. It provides new solutions for many basic problems in data mining and knowledge discovery, such as concept and knowledge representation, transition between qualitatives and quantitatives, concept synthesization and resolution, concept and concept hierarchy generation from data, etc. Cloud model is a model of the uncertain transition between a linguistic term of a qualitative concept and its numerical representation. Cloud model represents a qualitative concept with three digital characteristics, expected value Ex , entropy En and hyper entropy He , which integrate the fuzziness and randomness of a linguistic term in a unified way. This paper presents the fundamentals of cloud theory and its applications in spatial data mining and knowledge discovery, focusing on the cloud models and their algorithms.

关 键 词：云理论 云模型 云变换 空间数据发掘 知识发现 

分 类 号：TP311.13[自动化与计算机技术—计算机软件与理论]