计算欧几里德距离C语言源代码,次源码经测试可有效运行,源码简单易懂...

用VC++实现的BP（反向传播负反馈）神经网络算法-with VC BP (BP negative feedback) neural network algorithm

这是用matlab编的谱聚类程序，该方法能有效的用于数据分类。-This is a matlab procedures for the spectral clustering.The method is effective for data classification.

遗传问题的MATLAB代码,用于解决TSP问题的程序-Genetic problems MATLAB code for the procedure to solve TSP problems

标准的粒子群优化算法,visual c++.net环境下编写的代码,有助于学习和理解粒子群算法-Standard particle swarm optimization algorithm, visual c++. Net code to prepare an environment to help learning and understanding of particle swarm optimization

一个vc开发的支持向量机程序，对于初学者很有用．共享以下．-vc development of a support vector machine procedures, very useful for beginners. Sharing the following.

在国外网站上下的关于神经网络的原理理解原码-abroad on the site across the neural network theory to understand the original code

一个简单的fisher分类器代码,并含有实验用的两个数据集合.-a simple fisher classifier code, and contains the two experimental data sets.

3。《遗传算法与工程设计》，[日]玄光男着，程润伟着 科学出版社 2000年第一版 本书着重从计算方法和应用技术的角度对遗传算法作了深入浅出的讨论。书中介绍了遗传算法的基本概念和结构，解决约束优化和组合优化问题的方法，以及遗传算法在生产调度、可靠性设计、交通运输、设备布局等一系列工业工程问题中的应用。本书可作为高等院校的工业工程、管理科学、运等学、计算机科学和人工智能专业的本科生和研究生的教科书。对于系统分析员、运行研究员、管理科学家以及在工业工程与运筹学领域里从事最优化问题研究和应用的专业技术人员，本书也不失为一本内容丰富且实用性较强的参考书。-3. "Genetic Algorithms and Engineering Design", [] to Yuen-man, Guilin-a 520-531 2000 version of the first book to focus on calculation methods and application of a technical point of view for Genetic Algorithm a simple discussion. The book on genetic algorithms, the basic concepts and structures, optimization and constraint solving combinatorial optimization problems. and the genetic algorithm in production scheduling, reliability design, transportation, equipment and layout of a series of industrial engineering problems applications. The book can be used as colleges in the industrial engineering, management science, transport and other science, computer science and artificial intelligence professi

数据挖掘k-measextions 算算法，改进了其中部分结构。-Data Mining k-measextions counting algorithm, to improve some part of the structure.

基于梯度训练方法的rbf神经网络实现，采用随机训练及测试数据-Gradient-based training methods of rbf neural network, using a random training and test data