1) 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。
4) k-means clustering algorithm
K均值聚类算法
1.
Second, we study the structure of RBF neural networks and mathematical models, and initial create RBF neural network by using k-means clustering algorithm.
接着研究RBF神经网络的结构及数学模型,以K均值聚类算法确定RBF网络隐含层节点的中心、隐含层节点的宽度及输出权值等参数,初步建立RBF网络模型。
5) Particle swarm optimization K-means clustering algorithm
粒子群K均值聚类算法
6) parallel K-means clustering
并行K均值聚类算法
1.
This paper proposes a hardware/software partitioning algorithm of embedded system based on a parallel K-means clustering and greedy.
算法首先将有相似属性的任务节点通过并行K均值聚类算法组成一个大的任务节点,而后使用贪婪算法划分由大的任务节点组成的系统。
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。
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