而设置不合理的聚类参数又使得聚类结果质量变低。
It will output a low quality clustering result if user set unsuitable parameters before clustering operation.
该方法利用模糊似然函数对样本数据进行聚类，并使模糊模型的结构辨识和参数辨识能同时完成，从而实现模糊模型的在线辨识。
The proposed method can accomplish the structure identification and the parameter identification of the fuzzy model in the same time, and implements the on-line identification of the fuzzy model.
在RBF网络中采用了一种减聚类的学习算法来确定径向基函数的相应参数，使网络结构得到优化。
A learning algorithm of subtractive clustering for RBF network is used to obtain the parameters of radial basis function so as to optimize network structure.
在RBF神经网络中采用了一种减聚类的学习算法来确定径向基函数的相应参数，从而使神经网络结构得到优化。
A learning algorithm of subtractive clustering method for RBFNN is used to obtain the parameters of radial basis function, so that RBFNN has an optimized structure.
文中引入支持向量聚类（SVC）算法对多分量LFM信号进行检测和参数估计。
The support vector clustering(SVC)algorithm was introduced to detect linear modulation frequency(LFM) signal and estimate its parameter.
最后基于机理分析和模糊聚类技术建立了密闭鼓风炉过程操作参数优化决策模型。
Combining the mechanism analysis with Fuzzy Clustering technique, an optimization and decision-making model about operating parameters in the ISF smelting process is built.
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.
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.
本文从不同树种、不同时间、空间的分布出发，应用模糊聚类分区模型先对样本进行分类，以便确定有关参数。
The article applies fuzzy gathering distribution model and distribute species from different trees, time and space decides on the related parameter.
本文提出了一种新的基于有效性指数的聚类算法，无需提供聚类的参数。
In this paper, we propose a new clustering algorithm based on cluster validity indices, which obviates the needs for cluster parameters.
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.
模糊模型的前件和后件参数分别采用模糊C均值聚类（FCM）和正交最小二乘法（OLS）进行离线或在线辨识。
The T-S fuzzy model's parameters are identified by methods of fuzzy C mean(FCM) and orthogonal least-squares(OLS) online or otherwise.
引入减法聚类算法对样本数据进行分类，用得到的分类数据对局部模型参数进行离线辨识。
By introducing the subtraction clustering algorithm, the sample data are classified and the local model parameters are identified off-line using the corresponding data set.
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.
SVC算法中的核函数参数对聚类的形成起着决定性的作用，并影响着聚类的边界和形状。
Kernel parameter of the SVC algorithm plays an important role in clustering formation, which affects the boundary and shape of cluster.
粒子群优化聚类算法具有参数简单，收敛快等优势，但也有局部极值问题。
PSO clustering algorithm is known to have simple parameters and fast convergence, but there are also local optimal problems.
该方法是在原有模糊聚类法的基础上，推导出的在线自适应模糊推理算法，可应用在时变非线性系统参数在线辨识中。
The method is a kind of on line adaptive fuzzy reasoning which is deduced based on fuzzy clustering method. The method can be used in parameters identification of time-varying system.
对模糊聚类的方法进行了参数分析，引入指标保证了发电机分群的自适应性。
Analyze the parameters of the fuzzy clustering method, ensure the self-adaptive clustering of the generators by the fuzzy statistical index.
聚类分析方法利用距离系数的概念，把相关性较大的属性参数聚咸一类，使参数有一个正确的全面的分类。
Cluster analysis using the conception of distance parameter, made the attributes that have the high correlativity become the same sort. So the classification of attributes become complete and correct.
由于原始海量数据规模较大，聚类算法难以实现，而且聚类分析有时候只考虑关键属性作为分类参数。
The scale of original data is very large. It is difficult to realize the clustering algorithm. Clustering analysis often takes the key attributes as classification parameters.
从定义各类型车辆所占用的动态空间瞬时车道占有率入手，提出了以车辆瞬时占用车道长度与速度的比值为参数，基于模糊动态聚类对车辆进行分类的方法。
The paper analyzes the characteristics of fuzziness of dynamic space occupancy of different vehicles on urban arterials, and classifies the different vehicles by means of fuzzy clustering.
提出了一种用于基因表达数据的无参数聚类算法。
This paper proposed a new non-parametric algorithm for clustering gene expression data.
基于网格的参数自动化技术可以很好的处理传统网格聚类算法对参数敏感的问题；
PAG algorithm can solve the problem that the grid clustering algorithm is sensitive to parameters;
运用物元分析方法建立水质综合评价模型，采用灰色聚类方法确定各污染参数的权系数。
Matter element analysis has been used to create a Water Quality Comprehensive Assessment Model. The grey clustering method was used to calculate the weight of contamination.
方法将模式识别中的I SODATA聚类引入到中值滤波算法中，将分类的结果作为参数来确定如何进行中值滤波，以及是否需要进行中值滤波处理。
The result of clustering was set as the parameters to decide if median filter was necessary and when it was, how the process was to be carried out.
并采用聚类搜索、专家系统对生产目标函数进行了优化，以实现操作参数的优化控制。
And the target function was deduced. The optimization parameters was calculated using the cluster searching, expert system.
对输入参数作了详细的分析、筛选，并运用聚类算法对该模型进行了训练。
The network is trained by clustering algorithm. 120 sets of data were used for model building and validation.
对输入参数作了详细的分析、筛选，并运用聚类算法对该模型进行了训练。
The network is trained by clustering algorithm. 120 sets of data were used for model building and validation.
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