Combined Density-based and Constraint-based Algorithm for Clustering

We propose a new clustering algorithm that assists the researchers to quickly and accurately analyze data. We call this algorithm Combined Density-based and Constraint-based Algorithm （CDC）. CDC consists of two phases. In the first phase, CDC employs the idea of density-based clustering algorithm to split the original data into a number of fragmented clusters. At the same time, CDC cuts off the noises and outliers. In the second phase, CDC employs the concept of K-means clustering algorithm to select a greater cluster to be the center. Then, the greater cluster merges some smaller clusters which satisfy some constraint rules.Due to the merged clusters around the center cluster, the clustering results show high accu racy. Moreover, CDC reduces the calculations and speeds up the clustering process. In this paper, the accuracy of CDC is evaluated and compared with those of K-means, hierarchical clustering, and the genetic clustering algorithm （GCA）proposed in 2004. Experimental results show that CDC has better performance.     

W类态三纠缠原子与二项式光场相互作用过程中光场的量子特性

采用全量子理论, 研究处于W类态的三纠缠原子与二项式光场相互作用过程中光场的量子特性; 运用数值方法, 讨论了三纠缠原子初始状态和二项式光场系数对系统光场压缩和二阶相干特性的影响.     

一种基于改进径向基神经网络的人脸图像识别方法

常用于径向基神经网络中心参数学习的K-均值聚类算法,易受初始参数选取的影响而收敛于局部极小值.将自动终止聚类判据的减聚类算法用于径向基网络的学习,可根据样本集确定径向基函数数目,且其计算量与数据点的数目与考虑问题的维数无关,很适合于人脸这种维数较高的模式.实验证明,应用这种算法训练径向基神经网络识别人脸,从识别精度到识别速度上都优于传统算法.     

进入权--新的企业治理机制

阐述了企业内“权力”的演变过程,通过实例分析,指出进入权是一种优化资源配置的“类市场”机制,进入权的最终分配是市场上所有参与对象不断选择的结果。     

从语言文字看古诗英译

本文从英汉语言差异入手,论证了中国古诗意境美的形成和古汉语本身的属性和特征有着密切的关系,也正因为这种密切关系决定了古典诗歌的意境美在汉诗英译时是不可传译的.     

人力资源管理类课程教学刍议

本文通过对人力资源管理类课程的特点进行描述，提出了在该课程的教学中应运用案例教学法，并对案例教学法从概念、以及如何运用案例教学法进行了简要的论述。希望能够对从事该学科教学的教师有所帮助。     

一个已知结论f-1(σ(C))=σ(f-1(C))在命题证明中的应用

定理的重要性具体体现在命题的证明中.利用定理证明某些命题,会收到明显的效果,从而真正体现其作用.     

灰色统计方法在油田注水中的应用

利用灰色系统理论中的灰色统计方法,针对文南油田W33断块一些注水井的数据,确定了相应的灰类;通过对白化函数及灰数的计算,得到了该区块灰色决策矩阵,从而得到了该区块灰类的量化特征。所得结果可为油田决策者采取进一步的措施提供一定的理论根据。     

Identify Implicit Communities by Grap Clustering

How to find these communities is an important research work. Recently, community discovery are mainly categorized to HITS algorithm, bipartite cores algorithm and maximum flow/minimum cut framework. In this paper, we proposed a new method to extract communities. The MCL algorithm, which is short for the Markov Cluster Algorithm, a fast and scalable unsupervised cluster algorithm is used to extract communities. By putting mirror deleting procedure behind graph clustering, we decrease comparing cost considerably. After MCL and mirror deletion, we use community member select algorithm to produce the sets of community candidates. The experiment and results show the new method works effectively and properly.     

Base64编码的实现与应用研究

通过对Base64编码进行分析,及对实现两个主要类TBase64enCoder类、TBase64deCoder类进行剖析,更清楚了解实现算法的机理,并详细地解释了两个类的属性和方法,以利于编程中对它的正确了解和引用。