治疗基于代表点的聚类算法，一个数据挖掘算法…

标准遗传算法源码 C语言编程 求解函数优化问题。-Standard genetic algorithm C language programming for Function Optimization.

matlab神经网络应用设计，里面随有详细代码-Matlab neural network application design, which with a detailed code

java的神经网络工具箱-java nerve network toolbox

本程序是人工编写的bp神经网络，针对识别样本btw三类进行训练和识别。-This procedure is prepared bp artificial neural networks, btw samples for identification of three types of training and identification.

使用java构建神经网络的开源项目教程，是java爱好者学习神经网络的难得教材。虽然是英文教材，但是语言简单，易懂。书中前几章对于神经网络基本原理的讲解十分通俗易懂，利于初学者对相关知识的理解和吸收，即使不是java编程者，也可以从中受益匪浅。 -Using the java open source project to build neural networks tutorial java lovers are rare neural network learning materials. Although the materials are in English, but the language simple, easy to understand. The book for the first few chapters explain the basic principles of neural networks is very user-friendly, which will help beginners to understand and absorb the relevant knowledge, if not the java programmers can also be benefited from.

rbf网络一步预测matlab程序 精度还不错 很好用的 -rbf network matlab procedure step forecast accuracy is also very good with the bad

地球模拟器，最经典的人工生命模型,研究人工智能的必看。一般地说，生命都具有新陈代谢、复制和进化的能力。在自然界中，生物是由有限的食物供给和有限的生存空间约束的。在Tierra中，“生物”由一系列能够自我复制的机器代码或程序组成，它在计算机中的复制分别受到计算机的存储空间和CPU时间约束。能有效地占有内存空间和利用CPU时间的生物体，将具有更高的适应度，传递到下一代的机会就越大。 在Tierra中，计算机的RAM（随机访问存储器）中有一块专门的空间，这个空间中放置了一个“祖先有机体”，该祖先有机体根据它的汇编程序代码中的指令开始复制对它的生存是基本的代码。随着有机体的数目的增加，RAM中的空间减少了，因此有机体为了自己的生存空间开始竞争。-Earth Simulator, the most classic of artificial life model, the study of artificial intelligence Watchable. Generally speaking, life is metabolism, reproduction and the ability of evolution. In nature, biomass is limited by the supply of food and limited living space constraints. In Tierra, "biological" to a series of self-replicating machine code or procedure, in which computers were copied by the computer storage space and CPU time constraints. Effective occupy memory space and CPU time using the organisms, will have a higher degree of adaptability, conveying to the next generation the greater the chances. In Tierra, computer RAM (random access memory) is

KNN和BP的算法实现。输入一系列的样本值，进行训练和分类。源码是实现了两个分类器，已经调试通过-KNN and BP algorithm. Enter a series of sample values, for training and classification. Source is to achieve the two classifiers have been debugging through

是国外相关研究人员提供的发现频繁模式（包括频繁集、频繁子图等）的最新版本算法。-Foreign researchers with the relevant frequent pattern discovery (including frequent itemsets, frequent subgraph, etc.) the latest version of algorithm.

用Fast BP实现复杂的函数逼近,对初学者有一定的帮助,是在BP的基础上增加了R.-Fast BP achieved with a complex function approximation, there is some help for beginners, is based on the BP increase in R.