其次，把图像颜色空间聚类算法推广到广义图像；
Secondly, the algorithm of color cluster is extended to generalized image.
提出了一个基于数学形态学的三维空间聚类算法。
Based on mathematical morphology, a new algorithm of 3d spatial clustering was presented, which clustered spatial objects by closure operation.
DBSCAN是一种基于密度的空间聚类算法，在处理空间数据时具有快速、有效处理噪声点和发现任意形状的聚类等优点。
DBSCAN is a density based clustering algorithm that can efficiently discover clusters of arbitrary shape and can effectively handle noise.
该算法将具有足够高密度的区域划分为簇，并可以在带有“噪声”的空间数据库中发现任意形状的聚类。
It can handle spatial data and spot any-shape clusters in a noised spatial database by dividing them into clusters with high enough density.
针对异类传感器观测空间不一致的问题，提出了基于模糊聚类的异类多传感器数据关联算法。
For the inconsistency problem of heterogeneous sensors' measurement Spaces, a new data association (da) algorithm based on fuzzy clustering algorithm is presented.
为了实现复杂背景下的目标空间定位和尺度定位，提出了一种基于非参数聚类和多尺度图像的目标跟踪算法。
In order to track a target in space and scale in a complex background, a target tracking algorithm based on the nonparametric clustering and multi-scale images is presented.
利用Z曲线聚类和降维特性，本文给出网格划分方法、搜索区域分解过程，提出一种高维空间范围查询算法。
Based on Z curve, the paper presents a method of grid partition, a procedure of partitioning search region, and a high-dimensional spatial range query algorithm.
该模型利用模糊聚类技术确定系统的模糊空间和模糊规则数，利用BP算法调整模糊神经网络的权系数。
The fuzzy space and the number of fuzzy rules of this model are defined by the fuzzy clustering method and weight coefficients of the model are adjusted by the BP algorithm.
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.
实验结果表明，新算法较基于密度的带噪声数据应用的空间聚类方法(DBSCAN)具有更好的聚类性能。
Experimental results show that the new algorithm has better performance than Density Based Spatial Clustering of Applications with Noise (DBSCAN).
给出一种新的相似模式聚类算法，能高效地得到访问者对象在整个或者部分属性空间的相似访问行为模式。
The paper proposes a novel similar pattern clustering algorithm that can discover the pattern that exhibits a coherent pattern on a subset of dimensions.
该算法按照空间相邻关系，将空间相邻的空间目标聚类成一类。
The algorithm clusters neighboring spatial objects to a cluster on the neighborhood relation in spatial.
文中提出了一种基于DBSCAN的算法，可以处理非空间属性，同时又可以加快聚类的速度。
Proposes an improved DBSCAN algorithm which can handle non-spatial properties and greatly accelerate the speed of clustering.
本文介绍了地学空间数据迭代聚类的算法原理。
This paper presents algorithmic principles for approaching clustering of geo-spatial data.
算法首先对图像进行量化处理，而后在量化后的色彩空间中集成先验的分割信息进行色彩聚类。
The algorithm first has the image quantized and then clusters in the quantized color space with prior segmentation information.
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.
引入了一种新的基于网格的数据压缩方法，并应用该方法对处理大型空间数据集的聚类算法SGR IDS进行研究。
By introducing a new grid-based data compression framework, conducted the study on the clustering algorithm SGRIDS which dealed with a large spatial databases.
因此，可以考虑运用遗传算法来解决空间聚类问题。
So we can be considered the use of genetic algorithms to solve the problem of spatial clustering.
应用K均值自动聚类算法，提出了一种新的基于轨迹空间相似距离的轨迹分类算法，对以上获得的有效轨迹进行分类。
Using K Means which can automatically cluster trajectories, a new algorithm based on trajectory space similarity distance is presented, and it is applied to classify trajectory.
利用递推模糊聚类算法实时对系统的输入空间进行模糊划分，利用卡尔曼滤波算法确定参数。
The input space of fuzzy system is partitioned by means of real time recursive fuzzy clustering, and the parameters of fuzzy model are confirmed by Kalman filtering.
由于原始的模糊c -均值聚类算法没有考虑图像的空间信息，算法对图像中的噪音点十分敏感。
Without considering the spatial information of images, the original fuzzy C-means algorithm is very sensitive to image noise.
提出了一种以语言概念空间中的概念为聚类对象的信息检索方法以及适合于该方法的聚类算法。
An information retrieval model based on language concept space and a clustering method which serves the IR model is propsed.
为此，基于商空间的粒度分解和粒度合成原理，综合粗糙集和聚类算法对之进行改进。
Therefore, rough set and cluster methods are integrated based on granularity decompose and granularity synthesis theory of quotient space to improve this algorithm.
现有的半监督聚类方法较少利用数据集空间结构信息，限制了聚类算法的性能。
Most of the existing semi-supervised clustering methods neglect the structural information of the data, while the few constraints available may degrade the performance of the algorithms.
传统的FCM聚类算法未利用图像的空间信息，在分割叠加了噪声的MR图像时分割效果不理想。
However, the segmented results using the conventional FCM when dealing with noisy MR images are not satisfying because FCM takes no spatial information of images into account.
聚类分析是空间数据挖掘的一种方法，聚类算法能从空间数据库中直接发现一些有用的聚类结构。
Cluster analysis is a method of spatial data mining. Clustering algorithm can find some useful clustering structures directly from spatial data base.
该算法对特定领域的语料库进行反复的时间聚类和空间聚类，通过时间聚类发现语言片段的语法结构，通过空间聚类发现语言片段的语义类别；
Its grammar is produced by an iterative procedure, it spatially and temporally clusters the words from a domain-specific corpus. Temporal clustering can discover the fragment's syntactic structure.
该算法通过闭合运算，将空间对象聚成类，一次完成三维空间聚类，可以快速处理非凸的、复杂的聚类形状。
This algorithm could not only complete 3d spatial clustering at a time, and process clustering in-convex and complicated objects rapidly.
该算法通过闭合运算，将空间对象聚成类，一次完成三维空间聚类，可以快速处理非凸的、复杂的聚类形状。
This algorithm could not only complete 3d spatial clustering at a time, and process clustering in-convex and complicated objects rapidly.
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