1) K-means Cluster method
k均值聚类法则
2) K-Means clustering algorithm
K-均值聚类算法
1.
The learning of this method is divided into two processes,state space learning using K-means clustering algorithm for adaptive discretization of continuous states and policy learning using Sarsa algorithm for finding optimal policy.
该方法的学习过程分为两部分:对连续状态空间进行自适应离散化的状态空间学习,使用K-均值聚类算法;寻找最优策略的策略学习,使用替代合适迹Sarsa学习算法。
3) K-means clustering
K-均值聚类法
1.
Appliment of K-means clustering in condition monitoring of machinal equipment based on ferrograpny;
K-均值聚类法在机械设备铁谱监测技术中的应用
4) K-means clustering
K均值聚类算法
1.
Application of the improved K-means clustering algorithm in support vector machine;
改进的K均值聚类算法在支持矢量机中的应用
2.
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。
6) K-means clustering method
K~均值聚类法
1.
The logging-face was divided with K-means clustering method and logging-face dividing parameters which can reflect lithologic characteristic.
应用K~均值聚类法,进行测井相分析,依据岩性建立不同的渗透率模型,其相关性明显高于常规方法建立的渗透率解释模型,经计算得到的渗透率更接近于岩心分析数据。
补充资料：1,3-丁二烯低聚的均聚物
CAS：68441-52-1
中文名称：1,3-丁二烯低聚的均聚物
英文名称：1,3-Butadiene, homopolymer, oligomeric
中文名称：1,3-丁二烯低聚的均聚物
英文名称：1,3-Butadiene, homopolymer, oligomeric
说明：补充资料仅用于学习参考，请勿用于其它任何用途。
参考词条