基于模糊逻辑的异构地理空间数据集成决策支持系统

I. Mukherjee, S.K. Ghosh
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摘要

地理空间信息正在成为许多决策过程中不可或缺的一部分,特别是与社会经济发展有关的决策过程。地理空间数据通常由不同的组织收集和维护,成为空间集成的主要瓶颈。此外,各种空间对象之间的空间关系以及彼此之间的影响往往没有明确的定义。不同主题的数据之间存在着空间或主题关系。在现实世界中,推断不同主题数据之间的准确关系是不可能的。为了解决这种不准确性和不确定性,必须使用模糊逻辑概念。本文提出了一种利用模糊空间web服务集成这些不同数据的框架。该框架采用模糊地理空间数据模型对不同组织间的数据进行集成。该数据模型是基于基本特征集、领域知识和模糊逻辑建立的。利用领域知识衍生的不同主题数据与模糊逻辑之间的关联来映射这些不同数据之间关系的不确定性。利用模糊地理空间数据模型设计并填充了数据库。数据通过符合OGC(开放地理空间联盟)地理空间网络服务的企业GIS框架地理空间网络服务进行集成和访问。为了提供分析和决策支持,使用模糊逻辑概念实现了一个模糊决策系统。
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Integrating heterogeneous geospatial data for decision support system using fuzzy logic
The geospatial information is becoming an integral part of many decision making processes, specially related to socio-economic development. Geospatial data are often collected and maintained by different organizations and become a major bottleneck for spatial integration. Further, the spatial relationships between various spatial objects and the influence on each other are often not defined crisply. There exists a spatial or thematic relation between the data of different themes. In real world situations, inferring accurate relationship between the data of different themes is not possible. In order to address this inaccuracy and uncertainty, a fuzzy logic concept has to be used. In this paper, a framework has been proposed to integrate these diverse data using fuzzy spatial web services. The framework uses fuzzy geospatial data model to integrate the data across various organization. Such data model is developed based on base feature set, domain knowledge and fuzzy logic. The association between data of different themes derived from domain knowledge and fuzzy logic is used to map the uncertainties between the relationships of these diverse data. A database has been designed and populated using the fuzzy geospatial data model. The data are integrated and accessed through Enterprise GIS Framework geospatial web service that conforms to OGC (Open Geospatial Consortium) geospatial web services. For analysis and decision support a fuzzy decision system has been used implemented using fuzzy logic concepts.
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