主要研究音节基频包络的聚类问题。
In this paper, the clustering problem of syllable pitch contours is studied.
典型空间聚类问题的k值优化研究。
算法执行效率高，适合大规模数据的聚类问题。
The algorithm is efficient and can facilitate the clustering of a very large datas...
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.
实验表明，该算法对于解决数据流聚类问题非常有效。
Experimental results show that the algorithm is very effective to solve data stream clustering.
首先对基于多指标语言评价信息的聚类问题进行了描述；
Defining such problems and by virtue of the conventional fuzzy cluster analysis via digital information networking.
研究了具有参数优化的核函数法及其在聚类问题中的应用。
It studies kernel function method with parameters optimized and its application in pattern clustering.
面对满足二维空间邻接条件的聚类问题，定义了邻接矩阵的概念。
In order to dealing with the clustering considering the condition of planar adjacency relationship, the concept adjacency matrix is defined.
研究了基于样式相似性的子空间聚类问题，使用样式相似性作为相似性度量。
The problem of pattern-based subspace clustering, a special type of subspace clustering that uses pattern similarity as a measure of similarity, is studied.
聚类问题作为一种无监督的学习，能根据数据间的相似程度自动地进行分类。
As an unsupervised learning technique, dustering is a division of data into groups of similar objects.
系统研究了七种典型的空间数据聚类方法，积极探索基于约束条件的空间聚类问题的解决方案；
Seven kinds of spatial data clustering approaches are studied. And the technique to solve the problem of Constraint-based Spatial Cluster Analysis is explored.
数据流具有数据量无限且流速快等特点，使得传统的聚类算法不能直接应用于数据流聚类问题。
Data stream is characterized by infinite data and quick stream speed, so traditional clustering algorithm cannot be applied to data stream clustering directly.
然后成功地将聚类问题转换成蚁群求解问题，并使用基于蚂蚁觅食启发的蚁群算法进行聚类分析。
Then, the thesis USES ant colony algorithm which is based on the elicitation of ant's feeding to solve the clustering problem.
实验结果表明，该算法与DBSCAN是等价的，能更有效地解决批量数据更新时的增量聚类问题。
Experimental results show this algorithm is equal to DBSCAN, and can solve the increment clustering problem when the batch data is updated effectively.
为解决聚类数未知条件下面状地理实体的聚类问题，文中提出了一种基于聚类有效性函数的聚类方法。
A cluster validity function-based method is proposed for solving the problem of clustering for area geographical entities when the number of cluster is unknown.
在此基础上，设计和实现了人工免疫网络算法，并应用该算法成功解决了一个模式识别和数据聚类问题。
We design and implement the artificial immune network algorithm, and successfully apply this algorithm in solving a pattern recognition problem and a data clustering problem.
针对一类特征指标值及指标权重均为三角模糊数的多指标信息聚类问题，提出了一种新的最大树聚类分析方法。
With respect to multiple attribute clustering analysis problems with triangular fuzzy numbers, a new clustering analysis method is proposed.
本文对文本聚类问题的文本聚类算法进行了深入的讨论和研究，设计并实现了基于新算法的中文文本聚类系统。
The system of Chinese texts clustering based on new algorithm is implemented in this paper after discussion and research on format of texts vector and texts clustering algorithms.
针对高属性维稀疏数据聚类问题，提出高属性维稀疏信息系统概念，给出一种新的基于稀疏特征差异度的动态抽象聚类方法。
The concepts of high attribute dimensional information system are firstly proposed, and a new dynamic clustering method on the basis of sparse feature difference degree is presented.
本文研究了基于遗传算法和社会演化算法的数据挖掘和文本挖掘方法，主要包括数据挖掘和文本挖掘中的属性约简问题、聚类问题。
Several methods of data mining and text mining have been studied in this paper, which mainly includes: attribute reduction methods, clustering methods.
结果表明，神经元网络是用于解决采矿工程中权重评价、模式聚类问题的有效方法，对于解决采矿工程中相关问题有着广泛的应用前景。
Results show that Neural Network is an effective method for solving the weight evaluation, clustering analysis problem in mining and has widely spreading application prospect.
由于现实世界中时间序列多数是非线性的，而现有的时间序列聚类问题大多是基于线性时间序列模型进行聚类的，提出了可以用于非线性时间序列的聚类方法。
Most of the popular clustering methods are designed for the linear time series, assuming that the stationary time series can be fitted by linear model. In fact, the true word is nonlinear.
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.
在属性测度概念的基础上，运用属性聚类网络方法解决模式识别问题。
Based on concepts of attribute measurement, we used attribute clustering network approach to resolve some problems of pattern recognition.
聚类作为数据挖掘的一个问题已经受到了数据库团体的密切关注。
Clustering is a data mining problem that has received significant attention by the database community.
为了解决这一问题，利用改进的聚类方法，对匹配中心进行聚类，从而得到图形唯一的几何中心。
In order to solve the problem, we carry out the clustering operation to the matching centers by the improved clustering method, and thus get the unique geometry center.
为了解决这一问题，利用改进的聚类方法，对匹配中心进行聚类，从而得到图形唯一的几何中心。
In order to solve the problem, we carry out the clustering operation to the matching centers by the improved clustering method, and thus get the unique geometry center.
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