2implicit barrier based k-means algorithm
K-means
K-means算法是很典型的基于距离的聚类算法，采用距离作为相似性的评价指标，即认为两个对象的距离越近，其相似度就越大。该算法认为簇是由距离靠近的对象组成的，因此把得到紧凑且独立的簇作为最终目标。
K-means算法是硬聚类算法，是典型的局域原型的目标函数聚类方法的代表，它是数据点到原 型的某种距离作为优化的目标函数，利用函数求极值的方法得到迭代运算的调整规则。K-means算法以欧式距离作为相似度测度，它是求对应某一初始聚类中 心向量V最有分类，使得评价指标J最小。算法采用误差平方和准则函数作为聚类准则函数。 k个初始类聚类中心点的选取对聚类结果具有较大的影响，因为在该算法第一步中是随机的选取任意 k个对象作为初始聚类的中心，初始地代表一个簇。该算法在每次迭代中对数据集中剩余的每个对象，根据其与各个簇中心的距离将每个对象重新赋给最近的簇。当 考察完所有数据对象后，一次迭代运算完成，新的聚类中心被计算出来。如果在一次迭代前后，J的值没有发生变化，说明算法已经收敛。
算法过程如下： 1）从N个文档随机选取K个文档作为质心 2）对剩余的每个文档测量其到每个质心的距离，并把它归到最近的质心的类 3）重新计算已经得到的各个类的质心 4）迭代2～3步直至新的质心与原质心相等或小于指定阀值，算法结束
3Monte Carlo methods
http://en.wikipedia.org/wiki/Monte_Carlo_method
(or Monte Carlo experiments) are a class of computational algorithms that rely on repeated random sampling to compute their results. Monte Carlo methods are often used in simulating physical and mathematical systems. Because of their reliance on repeated computation of random or pseudo-random numbers, these methods are most suited to calculation by a computer and tend to be used when it is unfeasible or impossible to compute an exact result with a deterministic algorithm.[1]
Monte Carlo simulation methods are especially useful in studying systems with a large number of coupled degrees of freedom, such as fluids, disordered materials, strongly coupled solids, and cellular structures (see cellular Potts model). More broadly, Monte Carlo methods are useful for modeling phenomena with significant uncertainty in inputs, such as the calculation of risk in business. These methods are also widely used in mathematics: a classic use is for the evaluation of definite integrals, particularly multidimensional integrals with complicated boundary conditions. It is a widely successful method in risk analysis when compared with alternative methods or human intuition. When Monte Carlo simulations have been applied in space exploration and oil exploration, actual observations of failures, cost overruns and schedule overruns are routinely better predicted by the simulations than by human intuition or alternative "soft" methods.[2]
The term "Monte Carlo method" was coined in the 1940s by physicists working on nuclear weapon projects in the Los Alamos National Laboratory.[3]
4Van der Waals force
http://spspku.bjmu.edu.cn/Web%20Page/GeneralChem/kechengneirong/09/9-5-2.htm
3Monte Carlo methods
http://en.wikipedia.org/wiki/Monte_Carlo_method
(or Monte Carlo experiments) are a class of computational algorithms that rely on repeated random sampling to compute their results. Monte Carlo methods are often used in simulating physical and mathematical systems. Because of their reliance on repeated computation of random or pseudo-random numbers, these methods are most suited to calculation by a computer and tend to be used when it is unfeasible or impossible to compute an exact result with a deterministic algorithm.[1]
Monte Carlo simulation methods are especially useful in studying systems with a large number of coupled degrees of freedom, such as fluids, disordered materials, strongly coupled solids, and cellular structures (see cellular Potts model). More broadly, Monte Carlo methods are useful for modeling phenomena with significant uncertainty in inputs, such as the calculation of risk in business. These methods are also widely used in mathematics: a classic use is for the evaluation of definite integrals, particularly multidimensional integrals with complicated boundary conditions. It is a widely successful method in risk analysis when compared with alternative methods or human intuition. When Monte Carlo simulations have been applied in space exploration and oil exploration, actual observations of failures, cost overruns and schedule overruns are routinely better predicted by the simulations than by human intuition or alternative "soft" methods.[2]
The term "Monte Carlo method" was coined in the 1940s by physicists working on nuclear weapon projects in the Los Alamos National Laboratory.[3]
4Van der Waals force
分子间存在着一种只有化学键键能的1/10 ～ 1/100的弱的作用力，它最早由荷兰物理学家
van der Waals提出，故称van der Waals力。这种力对物质的物理性质如沸点、溶解度、
表面张力等有重要影响。按作用力产生的原因和特性，这种力可分为取向力、诱导力和色
散力三种。http://en.wikipedia.org/wiki/Van_der_Waals_force
http://spspku.bjmu.edu.cn/Web%20Page/GeneralChem/kechengneirong/09/9-5-2.htm
