地学数据集成及空间决策支持的方法与应用
GeoData Integration and Spatial Decision Making Based on Fuzzy Weights of Evidence and Weighted Logistic Regression
查看参考文献26篇
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文摘
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空间数据分析技术的严重滞后出现了“信息爆炸”的现象。因此，由于地学数据多源性的特点，如何集成量纲不一．形式多样，既有定量数据。又有定性的文字描述，经验性和知识性的地学数据并使之帮助决策成为当前亟待研究的课题之一。本文讨论两个空间数据集成和决策支持方法：模糊证据权重和加权逻辑回归方法。与传统地学数据集成和空间决策支持方法如判别分析和其他多元回归不同之处在于，这两种方法在解释变量是连续和类别变量混合模式的情况下或响应变量取两类值的情况下处理的结果更为合理。 |
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其他语种文摘
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How to integrate quantitative data, qualitative data, empirical data and knowledge-based data and then make decision is one of the important issues in spatial data analysis. In this paper, two methods for spatial integration and decision making are discussed. One is fuzzy weights of evidence, and the other is weighted logistic regression. Compared with the traditional methods such as discriminate analysis and multivariate regression analysis, these two methods can give more reasonable results when explanatory variables are a mixed mode of continuous and category data. |
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来源
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地球信息科学
,2006,8(1):16-20 【扩展库】
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关键词
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空间数据集成
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模糊证据权重
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加权逻辑回归
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空间决策支持
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地址
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中国科学院地理科学与资源研究所, 北京, 100101
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语种
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中文 |
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文献类型
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研究性论文 |
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ISSN
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1560-8999 |
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学科
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测绘学;自动化技术、计算机技术 |
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基金
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国家自然科学基金
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中国科学院知识创新工程领域前沿项目
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文献收藏号
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CSCD:2307843
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26
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