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Paper about spatial data mining that explain in detail.
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Paper about spatial data mining that explain in detail.
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Paper about spatial data mining that explain in detail.
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Paper about spatial data mining that explain in detail.
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Paper about spatial data mining that explain in detail.
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实现空间数据挖掘中的关联规则，代码短小但精炼，已经被作者成功实现。-Spatial data mining association rules, the code short, but refined, has been a successful author.
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目前三角网是进行精细地形表达最好和最常用的方法，因此本文讨论利用三角网法来建立露天矿的精细DEM模型。由于露天矿复杂特殊的地形特征，在建模过程中应充分考虑相应的约束条件，否则会出现台阶被削平等现象。构建不规则三角网的方法可分为分而治之算法、逐点插入算法和三角网生长算法。各种算法各具优缺点，结合矿区的实际情况，本文采用一次性约束三角网生成算法，经过空间数据提取、拓扑关系建立以及空间索引建立，最终建立起边界约束线以内的约束不规则三角网。-At present, triangulated irregu
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本文首先介绍了粗糙集理论的基本概念，包括等价关系、不可分辨关系、上下近似、粗糙集和简约；并且从空间数据挖掘、遥感影像处理、GIS 不确定性、GIS 数据分析、模糊地理对象建模和粗糙集与其它软计算方法的结合等六方面概述了粗糙集理论在GIS 数据处理中应用的进展-This paper introduces the basic concepts of rough set theory, including the equivalence relation, can not distinguish be
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本文首先介绍了粗糙集理论的基本概念，包括等价关系、不可分辨关系、上下近似、粗糙集和简约；并且从空间数据挖掘、遥感影像处理、GIS 不确定性、GIS 数据分析、模糊地理对象建模和粗糙集与其它软计算方法的结合等六方面概述了粗糙集理论在GIS 数据处理中应用的进展-This paper introduces the basic concepts of rough set theory, including the equivalence relation, can not distinguish be
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一种空间数据挖掘查询索引的设计A spatial data mining query the index design-A spatial data mining query the index design
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讲述空间数据挖掘的相关知识，前景-About the knowledge of spatial data mining, prospect, etc.
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空间数据挖掘— 空间数据挖掘-Spatial data mining- data mining- data mining
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城市空间数据挖掘方法与应用,主要介绍城市相关地理信息的挖掘算法与实现,希望对大家有帮助-Urban spatial data mining methods and applications, focuses on the city' s geographic information related to mining algorithms and implementation, we want to help
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空间聚类算法GDBSSCAN 对数据挖掘有用
-Spatial clustering algorithm GDBSSCAN useful data mining
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KMEAN C#
In data mining, k-means clustering is a method of cluster analysis which aims to partition n observations into k clusters in which each observation belongs to the cluster with the nearest mean. This results in a partitioning of the data sp
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In data mining, k-means clustering is a method of cluster analysis which aims to partition n observations into k clusters in which each observation belongs to the cluster with the nearest mean. This results in a partitioning of the data space into Vo
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Crime hot-spot location prediction is important for public safety. The output from the prediction
can provide useful information to improve the activities aimed at detecting and preventing
safety and security problems. Location prediction is a sp
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数据挖掘算法 dbscan 基于密度的聚类算法 它将簇定义为密度相连的点的最大集合，能够把具有足够高密度的区域划分为簇，并可在噪声的空间数据库中发现任意形状的聚类-Data mining algorithms dbscan density-based clustering algorithm will cluster is defined as the density of points connected to the largest collection of regional divisi
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Mining trajectory data has been gaining significant interest in recent years. However, existing approaches to trajectory
clustering are mainly based on density and Euclidean distance measures. We argue that when the utility of spatial clustering of
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Spatial data mining seminar presentation for my seconed degree in information technology.
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