为了克服传统FCM算法的局限性，本文提出了一种基于空间邻域信息的二维模糊聚类图像分割方法（2DFCM）。
In order to overcome the limitation of FCM, a novel Two-dimension Fuzzy Cluster Method (2DFCM) was proposed based on the spatial information.
另外用基的邻域约定给出了单调正规空间的一个等价刻划。
Also gives an equivalent condition of monotonically normal Spaces USES of the concept of neighborhood assignment of base.
本文改进了传统FCM的目标函数，引入控制邻域作用紧密程度的参数，提出了一种能够更加合理地运用图像的空间信息，改进的模糊c -均值聚类算法。
Modifying the objective function of FCM and introducing a variable as the parameter to control the tight degree of neighborhood effect present a spatial model to FCM clustering algorithm.
用集合近似邻域为手段，研究了知识论域拓扑空间，得出了一些重要结论。
The knowledge universe topology Spaces are studied by set approximate neighbourhood, and many important conclusions are achieved.
引入覆盖空间，定义了其邻域、内部、闭包、测度等概念，研究了它们的性质。
In this paper covering space is introduced. The notions, neighborhood, interior, closure and measure, are defined, and the properties of them are studied.
比较邻域结构、均匀场近似、偶对近似、以及入侵概率分析的数学方法也被用来研究空间博弈模型。
In spatial game models, mathematical methods of comparing the local payoff structures, mean-field approximation, pair approximation, as well as invasion probability analysis are also used.
算法局部搜索过程中采用的基于关键路径的邻域结构缩小了问题的搜索空间。
The critical block based neighborhood structure of the problem in the local search procedure reduces the searching space of the problem and increases the probability of ants finding good solutions.
方法通过建立估值点周围邻域点间空间分布权系数的函数，确定参与克立格估值计算的邻域点。
In order to optimize the algorithm of selecting Kriging neighborhood points, this paper introduces a new algorithm based on space distribution weight coefficient.
本文主要讨论遥感图象空间邻域结构信息分析方法。
This paper is about the remote sensing image analysis using spatial contextual in-formation.
实验结果表明，该方法能够快速甄别边界像元和邻域像元，比同类算法拥有更高的空间影像检索速度。
The results show that the method can distinguish boundary image-element and neighborhood image-element rapidly, and has a higher rate than other similar algorithms.
结合粗糙集理论和遥感数据中地物光谱特征空间分布信息，提出了一种基于光谱特征邻域的容差粗糙集分类方法，用来处理卫星遥感数据分类中的不确定性问题。
Based on the spectral feature neighborhood, this paper proposes a tolerant rough set classification method to handle the uncertainty in the process of satellite remote sensing data classification.
结合粗糙集理论和遥感数据中地物光谱特征空间分布信息，提出了一种基于光谱特征邻域的容差粗糙集分类方法，用来处理卫星遥感数据分类中的不确定性问题。
Based on the spectral feature neighborhood, this paper proposes a tolerant rough set classification method to handle the uncertainty in the process of satellite remote sensing data classification.
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