本程序实现了一个人工神经网络的算法，相关领域的人可以参考。...

本人编写的incremental 随机神经元网络算法，该算法最大的特点是可以保证approximation特性，而且速度快效果不错，可以作为学术上的比较和分析。目前只适合benchmark的regression问题。 具体效果可参考 G.-B. Huang, L. Chen and C.-K. Siew, “Universal Approximation Using Incremental Constructive Feedforward Networks with Random Hidden Nodes”, IEEE Transactions on Neural Networks, vol. 17, no. 4, pp. 879-892, 2006. -I prepared by incremental random neural network algorithm, which is characterized by the largest approximation properties can be guaranteed, and fast good results can be used as an academic comparison and analysis. The current benchmark is only suitable for the regression problem. Specific effects may refer G.-B. Huang, L. Chen and C.-K. Siew,

vb写的改进的遗传算法程序。是一些通用代码，与具体问题对应的代码空出来，用的时候填进去。根据我的经验，要想用好遗传算法，代码必须自己写，因为问题不同，编码，杂交，变异算子可能都不一样。特别是杂交算子，需要根据问题调整，甚至创造出新的杂交方法。而且适应度计算的代码也需要自己写，特别是带约束的优化问题 -vb write improvement in the genetic algorithm. Some common code, with the specific issues the corresponding code space, and the time spent filling into account. According to my experience, in order to make good use of genetic algorithms, code must write their own, because different issues, coding, hybridization and mutation operator may not like. In particular hybrid operator, the need to adjust the problem, or even create a new hybrid method. But fitness calculation of the code required to write their own, especially with the constrained optimization problem

一个神经网络BP算法源码-a neural network algorithm source code

采用“提前停止”方法提高 BP 网络的推广能力。对于和例 2相同的问题，在本例中我们将采用训练函数 traingdx -The use of

John Wiley & Sons,.Fuzzy Engineering Expert Systems with Neural Network Applications.[2002.ISBN0471293318]

模式识别中关于C均值的聚类算法的程序,输入点进行聚类.-pattern recognition on the C-means clustering algorithm procedures input cluster.

首先采用某种编码方式将解空间映射到编码空间，每个编码对应问题的一个解，称为染色体或个体。一般通过随机方法确定起始的一群个体，称为种群，在种群中根据适应值或某种竞争机制选择个体，使用各种遗传操作算子产生下一代如此进化下去，直到满足期望的终止条件。-begin using some form of coding mapping to the solution space coding space, each encoding a corresponding solution to the problem, known as chromosome or individual. General randomly determined by the initial group of individuals, called stocks, the stocks based on fitness or some mechanism to choose the individual competition, the use of genetic Operator evolution of the next generation so on, until the termination meet expectations conditions.

c++编写的模式识别k均值算法-c k prepared by the average pattern recognition algorithm

vs2005开发 遗传算法求解144城市的旅行商问题-VS2005 to develop genetic algorithm 144 city traveling salesman problem

程序包含的设置包括：列数、样本总个数、建模样本数、预报因子数、预报对象数、学习因子、 动量因子、训练次数、总体误差、隐节点数。-procedures contained in the set include : number, the total sample number, the number of samples modeling, forecasting several factors, forecasting several targets, learning factor, momentum factor, the number of training, the overall error of hidden nodes.