multi

围绕粒子群的当前质心对粒子群重新初始化.这样，每个粒子在随后的迭代中将在新的位置带着粒子在上次搜索中获得的“运动惯性”（wvi）向Pi，Pg的方向前进，从而可以在粒子群的运动过程中获得新的位置，增加求得更优解的机会.随着迭代的继续，经过变异的粒子群又将趋向于同一点，当粒子群收敛到一定程度时又进行下一次变异，如此反复，直到迭代结束.-particle swarm around the center of mass of the current PSO reinitialization. Thus, Each particle in the next iteration will be in the new location with particles in the last search was the "inertia" (wvi ) Pi, Pg orientation, and thus can PSO course of the campaign was a new position, increase seek better solutions opportunities. With the continued iteration, after variation of PSO will tend to the same point. When PSO converge to a certain extent when the next variation, so repeatedly, until the end of iteration.

kalyp是人工生命和神经网络方面架构最全的代码，对于进行仿真代码实现很有参考价值。-kalyp of artificial life and neural network architecture of the entire code for simulation code to achieve great reference value.

SPEA2源码，效果相当好 ZIZTLER系列复杂函数只有第三个效果不太好-SPEA2 source, the effect ZIZTLER very good series of complex functions, only the third effect is not a good

用于multivariate时间序列分类，利用了weka机器学习系统（本站可下载）-for multivariate time series classification, the use of machine learning system weka (site available for download)

Fisher线性判别分类器源代码，包括训练函数和测试函数。-Fisher Linear Discrimination (FLD) classifier source code, including training function and test function.

经典的SOM人工神经网络例子源码，经测试可用，可作入门学习用-SOM classic examples of artificial neural network source code

对著名的UCI机器学习库的wine数据集做的朴素贝叶斯分类算法，包含详细源代码和实验报告，不可多得啊-Pairs of well-known UCI machine learning repository data set to do wine Naive Bayesian classification algorithm, with detailed source code and test reports, a rare ah

蚁群聚类算法,用于计算数据聚类的程序,还未实验效果-Ant colony clustering algorithm, used to calculate the data clustering procedure, yet the experimental effect

fortran版 神经网络遗传算法-fortran version of neural network genetic algorithm

网络为３层结构，输入层为６个神经元，隐含层为４个神经元，输出层为１个神经元，当输入层为中心对称样本 1，0，0，0，0，1等时，网络输出为1，否则输出为0。-network of three-layer structure, input layer to six neurons to the hidden layer 4 neurons, the output layer to a neuron, when the input layer to the center symmetry samples such as 1,0,0,0,0,1, the output of a network, the output is 0.