This is a pattern recognition in a simple window parzen Category simulation exam...

移动机器人运动学mathematica程序-Mobile robot kinematics mathematica program

求最优值的一个算法-seeking an optimal value of the algorithm

基于股票的程序-Stock-based procedures

智能电动小车的程序，包括光源检测，黑线检测，障碍物检测等-Smart electric car procedures, including light detection, and line detection, obstacle detection, etc.

apriori算法是数据挖掘的经典算法之1,其基于关联规则的思想.这是我的第2个收藏算法-algorithm is data mining algorithms of a classic algorithms, based on the idea of association rules. This is my first two collections Algorithm

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

模式识别以及重要问题，很好的内容，千万不要错过-Pattern recognition, as well as important issues, very good content, do not miss

利用一个较为成熟的遗传算法基础类库（作者:刘康），我自己在做论文的时候写得一个关于利用遗传算法进行节点部署应用的实验程序。您可以很容易地在其基础上实现自己应用相关的算法程序，进行研究验证工作。希望此源码能够为相关人事提供帮助。-Use of a more mature class library based on genetic algorithm (Authors: Liu Kang), I have to do when writing a thesis on the use of genetic algorithm application node deployment Experimental procedures. You can easily realize in their own applications based on the algorithm-related procedures, conduct research validation. I hope that this source can provide assistance for the relevant personnel.

粒子群优化算法(PSO)是一种进化计算技术(evolutionary computation).源于对鸟群捕食的行为研究 PSO同遗传算法类似，是一种基于叠代的优化工具。系统初始化为一组随机解，通过叠代搜寻最优值。但是并没有遗传算法用的交叉(crossover)以及变异(mutation)。而是粒子在解空间追随最优的粒子进行搜索。详细的步骤以后的章节介绍 同遗传算法比较，PSO的优势在于简单容易实现并且没有许多参数需要调整。目前已广泛应用于函数优化，神经网络训练，模糊系统控制以及其他遗传算法的应用领域-Particle Swarm Optimization (PSO) is an evolutionary technology (evolutionary computation). Predatory birds originated from the research PSO with similar genetic algorithm is based on iterative optimization tools. Initialize the system for a group of random solutions, through iterative search for the optimal values. However, there is no genetic algorithm with the cross- (crossover) and the variation (mutation). But particles in the solution space following the optimal particle search. The steps detailed chapter on the future of genetic algorithm, the advantages of PSO is simple and easy to achieve without many parameters need to be adjusted. Now it has been widely used function optimization, neural networks, fuzzy systems control and ot

设计的bp神经网络，来判断和预测机器的故障级别。-Bp neural network designed to determine and predict the fault-level machines.