Using gray clustering method to determine station number of districts, then on the site plan for further optimization.
采用灰色聚类方法确定各影响区县的站点数量，然后对选址方案做进一步的优化。
The excellent and defect of gray clustering models in existence were analyzed and the mechanism of the original model was demonstrated in the letterpress.
分析了现有主要灰色聚类模型的优缺点，论证了灰色聚类原模型的机理。
The Concentration data of QINDAO atmosphere was analyzed with gray clustering method and the correctness of the analyzed results was judged with variance theory.
对青岛大气中氯离子浓度数据进行了灰色聚类分析，采用方差理论判定聚类结果的正确性，并对比分析了万宁氯离子数据的灰色聚类结果。
The number field continuation was adopted by information acquire ability sub index, and the gray comprehensive clustering coefficients of relative objects were also acquired.
将信息获取能力分指标取数域延拓，求得相关对象关于灰类的综合聚类系数。
Results Fuzzy K means clustering algorithm can segment white matter, gray matter and CSF better from the MR head images.
结果模糊K- 均值聚类算法能很好地分割出磁共振颅脑图像中的灰质、 白质和脑脊液。
This thesis deals with gray image. The kernel of segmentation is pixel clustering. It belongs to optimization problem.
本文处理的对象是灰度图像，分割的核心是对像素进行聚类，属于优化问题。
Applying the gray fixed-weight clustering method to evaluate the safety level of the sample road networks which was given in the chapter 3.
利用3种路网在各种类型的攻击情况下的失效程度的数据，应用灰色定权聚类判别法对其进行了计算，以得到各种类型路网的安全等级。
According to the characters of the images, the algorithm separated image into several regions by K-means clustering algorithm, and each region is equalized respectively within their gray levels.
该算法基于图像的特点，利用K均值聚类算法将图像分成几个灰度区间，然后再分别进行均衡化。
A new algorithm method of image enhancement based on K-means clustering is presented, according to the characteristics of infrared gray-image.
根据红外灰度图像的特点，提出了一种基于K -均值聚类的图像增强的新算法。
A new algorithm method of image enhancement based on K-means clustering is presented, according to the characteristics of infrared gray-image.
根据红外灰度图像的特点，提出了一种基于K -均值聚类的图像增强的新算法。
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