由于K－均值聚类算法局部最优的特点，而模拟退火算法理论上具有全局最优的特点。因此，用模拟退火算法对聚类进行了改进。20组聚类仿真表明，平均每次对K结果值改进8次...

SVM分类器，由上海交通大学编写，软件使用方便、好用-SVM classifier, from the preparation of the Shanghai Jiaotong University, the software easy to use, handy

This toolbox contains re-implementations of four different multi-instance learners, i.e. Diverse Density, Citation-kNN, Iterated-discrim APR, and EM-DD. Ensembles of these single multi-instance learners can be built with this toolbox

利用模拟退火法求解TSP问题 可以求得50个城市的精确解-The use of simulated annealing algorithm for solving TSP problems can be obtained 50 cities Exact Solutions

rhapsody in C++企业解决方案-rhapsody in C++ Enterprise Solutions

用java编写的bp网络和rbf网络的源程序 JNNT由java语言写成，具有跨平台的优越性能.java applet的演示版更简单到只需要任何机器上的浏览器就可以运行，无需安装任何大型附加软件。更方便爱好者通过internet远程访问资源。 -with java bp prepared by the network and the networks of the source rbf JNNT by java language, cross-platform advantages can be. java applet demo version of a more simple to just any machine on the View All can be run without having to install any additional software major. Lovers more convenient remote access through the internet resources.

模拟退火算法 模拟退火算法(Simulated Annealing,简称SA算法)是模拟加热熔化的金属的退火过程，来寻找全局最优解的有效方法之一。 模拟退火的基本思想和步骤如下： 设S＝{s1,s2,…,sn}为所有可能的状态所构成的集合， f：S―R为非负代价函数，即优化问题抽象如下： 寻找s*∈S，使得f(s*)＝min f(si) 任意si∈S （1）给定一较高初始温度T，随机产生初始状态S （2）按一定方式，对当前状态作随机扰动，产生一个新的状态S’ S’＝S＋sign(η).δ 其中δ为给定的步长， η为[－1,1]的随机数-simulated annealing algorithm (Simulated Annealing, or SA algorithm) is a simulation of heating molten metal in the annealing process, to find the global optimum one of the effective ways. Simulated Annealing basic ideas and the steps are as follows : S = (s1, s2, ..., sn) for all possible state posed by the pool, f : S-R non-negative cost function, that is abstract optimization problems are as follows : Find S* s, making f (s*) = min f (si) arbitrary si S (1) to set a higher initial temperature T, randomly generated initial state S (2) of a certain form, the current state of random disturbance, have a new state S "S" = S+ sign (). delta where given for the step, [-1,1] Random Number

清华大学不确定规划教材中的用遗传算法训练神经元网络的混合智能算法1-Tsinghua University, uncertainty in the planning of teaching materials by using genetic algorithm trained neural network Hybrid Intelligent Algorithm 1

此代码是用c语言编写的决策树的c4.5代码，它是数据挖掘分类算法中的一种，可以对给定数据集进行分类，挖掘出规则-this code is c language of the decision tree Bank code, which is data mining classification algorithm of a can of a given data set for classification, tapping rules

支持向量机工具箱使用方法演示，讲述如何使用svm的工具箱。-Support Vector Machines to use the toolbox demonstration on how to use the toolbox svm.

利用pso算法训练人工神经网络的源代码。-PSO algorithm for the use of training artificial neural network source code.