height 遗传身高计算 根据父母的升高计算后代身高

王小平《遗传算法――理论、应用与软件实现》随书光盘，内容有： GA 本书中所附源程序C或C++代码文件及其可执行文件 Scs.cpp 基本分类算法源程序，输入数据文件cfile.txt,efile.txt,gfile.txt,pfile.txt,rfile.txt,tfile.txt Sga.c 基本遗传算法源程序, 输入数据文件input，输出文件output A_life.c 基于遗传算法的人工生命模拟源程序, 输入数据文件world GA_nn.c 基于遗传算法优化神经网络结构源程序,输入数据文件sample Patmat.c 基于遗传算法提取基元图形源程序 Sources 遗传算法相关自由软件及代码。-Wang Xiaoping,

径向基网络对Polynomial函数的逼近和拟合-Radial basis function networks Polynomial Approximation and fitting

股票选择的遗传算法-stock options Genetic Algorithm

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

实现了一般表达式的合一算法（采用最一般合一求取方法）-achieve a general expression of unity algorithm (to use the most general strike Ecumenical methods)

本程序是关于qam的解调程序用c语言编写希望大家能用-this process is on the demodulation process qam c language with hope everyone can be prepared

SOM人工神经网络的经典例子源代码，是真的

多层神经网络范例 http://www.codeproject.com/cpp/MLP.asp?df=100&forumid=148477&exp=0&select=1141594#xx1141594-multilayer neural network model http :// www.codeproject.com/cpp/MLP.asp df = 1

已知北京、上海、广州、昆明和西安五城市航线里程如图。分别实现： 1）找到北京到昆明的最短路径。 2）找到北京到昆明，必须途径上海的路径。 3）找到北京到昆明，必须途径上海，但不能去广州的路径。 -known Beijing, Shanghai, Guangzhou, Kunming and Xi"an City route five mileage figure. Were achieved : 1) to Kunming to Beijing to find the shortest path. 2) find Beijing to Kunming, Shanghai must channel"s path. 3) to find Beijing to Kunming, Shanghai must channels, but can not go to Guangzhou"s path.

改进遗传算法－郭涛算法做最优化问题很管用,算法的基本思想是 先任意产生n个随机数，然后从n个数里随机选择m个数，再有这m个 数合成一个新数，将这个新数同n个数中间适应值函数值的最差的比较， 如果好的话就取代最差的那个，如果它比最好的还要好的话，则把最好的 也取代。如果比最差的坏，则重新合成一个新数。依次循环下去。 程序的奇妙之处是GA_crossover()函数，产生的新数确实比较好，看看 那位大侠能改进一下，产生比这跟好的数。-improved genetic algorithm- Guo Tao done optimization algorithm is very effective, and the algorithm is the first basic idea arbitrary n generated random number and then the number li n m randomly selected number, and this number m of a new synthesis of the new middle with n number fitness function of the worst by comparison, if a good case to replace the worst, um, if it even than the best, then ruled the best have replaced. If worse than the worst, a de novo synthesis of new. Followed by the cycle continues. The magic of procedures is GA_crossover () function, the new really good to see heroes who can be improved upon, it generated more than a few with a good.