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基于模糊神经网络的模糊空间对象生成方法研究
引用本文:张辉,杨俊涛,李参海.基于模糊神经网络的模糊空间对象生成方法研究[J].东北测绘,2008,31(1):1-3.
作者姓名:张辉  杨俊涛  李参海
作者单位:[1]中国矿业大学环境与测绘学院,江苏徐州221008 [2]中国测绘科学研究院重点实验室,北京100039 [3]黑龙江第三测绘工程院,黑龙江哈尔滨150086
基金项目:国家自然科学基金(40571127)资助
摘    要:随着对GIS中的空间对象模型和自然地理特征表达的研究深入,模糊空间对象被提出。针对模糊空间对象表达的特点,提出了一种基于模糊神经网络的模糊空间对象生成方法。该方法将模糊技术与神经网络相结合,利用神经网络的学习能力调整模糊隶属函数和模糊规则,使系统具备自适应的特性。实验表明,这种基于模糊神经网络的生成模糊空间对象的方法比传统方法大大的提高了成果的精度。

关 键 词:模糊空间对象  模糊神经网络  模糊土地覆盖
文章编号:1672-5867(2008)01-0001-03
收稿时间:2007-09-20

Research on the Generation Method of Fuzzy Spatial Objects Based on Fuzzy Neural Networks
ZHANG Hui , YANG Jun - tao, LI Can - hai.Research on the Generation Method of Fuzzy Spatial Objects Based on Fuzzy Neural Networks[J].Northeast Surveying and Mapping,2008,31(1):1-3.
Authors:ZHANG Hui  YANG Jun - tao  LI Can - hai
Institution:ZHANG Hui , YANG Jun - tao, LI Can - hai ( 1. School of Environment Science & Spatial Informatics, China University of Mining Technology, 2. Chinese Academy of Surveying and Mapping, Beijing 100039, China; 3. The Third Heilongjiang Engineering Institute of Surveying and Mapping, Harbin 150086, China)
Abstract:With the deep research on the spatial objects model of GIS and the representation of natural geographical feature, this paper put forward the fuzzy spatial objects. Referring to the characteristics of the representation of fuzzy spatial objects, it also brought forward a generation method of fuzzy spatial objects based on fuzzy neural networks. By combining the fuzzy technology and neural networks, utilizing the learning ability to enhance the fuzzy Membership Function and fuzzy rules, the system will be self - adaptive. From the experiments of this paper, by comparing with the traditional fuzzy objects generation, the method in this paper improved the accuracy of results.
Keywords:fuzzy spatial objects  fuzzy neural networks  fuzzy land cover
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