用BP神经网络逼近函数Z=SIN(X*Y),采用C++编程.

遗传优化神经网络结构，C++源代码-Genetic optimization of neural network architecture, C++ Source code

识别数据集,可以用来作为,分类的实验数据.类别:模式识别-Identification of data sets, can be used as, the classification of experimental data. Category: Pattern Recognition

java extreme programming cookbook

AI 人工智能 在C#环境下 实现 过河问题 算法-AI

本程序用国外流行的NetLogo开发，模拟蚂蚁群寻食-this program popular with foreign NetLogo development, simulation Ant group ants

以一个简单的例子说明模拟退火算法的思想。 模拟退火法求函数f(x,y) = 5sin(xy) + x^2 + y^2的最小值，对理解模拟退火算法是一个很好的程序示例。-to a simple example illustrates the simulated annealing algorithm thinking. Simulated Annealing for the function f (x, y) = 5sin (xy) x ^ 2 y ^ 2 minimum, the right understanding of simulated annealing method is a good example of the procedure.

一个高人的VC实现NN的程序。很不错。先运行Matrixbase.dsw,again arithmetic.dsw, next nnbp.dsw,final neuralNetWork.dsw.-an expert in VC NN procedures. Very good. First running Matrixbase.dsw, again arithmetic.dsw. next nnbp.dsw, final neuralNetWork.dsw.

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.

带有QoS约束的组播路由问题是一个NP完全问题，遗传模拟退火算法是遗传算法和模拟退火算法的一种融合，可以为这类问题提供一个解决方案-With QoS constraint multicast routing problem is an NP-complete problem, genetic simulated annealing algorithm is a genetic algorithm and simulated annealing algorithm as a fusion, you can provide for such a solution

利用动量梯度下降算法训练BP网络，得到误差显示图，并最终进行预测-Gradient descent algorithm using momentum BP network training, the error display map, and, ultimately, to predict