遗传算法的源程序，里面有基本的遗传算法的各种操作过程，很全面！...

介绍模拟退火算法的经典资料，最后附了一些经典的例子-Describes the classic simulated annealing algorithm information, finally attached to a number of classic examples of

五子棋是一种受大众广泛喜爱的游戏，这里介绍五子棋程序的数据结构、评分规则、胜负判断方法，重点分析了搜索算法，并在传统的博弈算法在五子棋应用中进行一些改进，从而使剪枝更有效，运算性能更好。改进包括：不使用closed表；改变棋盘搜索顺序；增加记录最大棋盘信息的指针。实验证明，这几点改进对提高效率有很高帮助。

【机器学习】文本分类源代码 【机器学习】文本分类源代码 -] [Machine learning text classification source code] [machine learning text classification source code

资源分配神经网络解决Mackey-Glass时间序列预测函数逼近问题-Neural network to solve the allocation of resources Mackey-Glass time series prediction function approximation problem

遗传算法神经网络，遗传算法神经网络遗传算法神经网络-genetic algorithm neural networks, genetic algorithms neural networks, genetic algorithm, neural network

< 神经网络设计源代码>>一书的源代码。-err

This software was done in part for a textbook on AI I ve written called _The Basis of AI_ (tentative title, subject to change but not if I get my way). For details see: http://www.mcs.com/~drt/basisofai.html

这是一个二值hopfield神经网络源程序，有一个实例，训练数据保存在h7x8n4.trn,输出数据保存在ARCHIVE.LST中。-This is a value hopfield two neural network source, an example of training data stored in h7x8n4.trn, output data stored in ARCHIVE.LST China.

提出了基于最小化估计的泛化误差界非优化估计方法。目前大多数的核参数选择方法都是通过极小化了来得到最优参数值，但是求解优化问题的计算代价相当的大，并且不能很好地体现数据的分布特征。本文采用非优化技术，通过极小化泛化误差来优化核及相关参数，由于直接计算最小半径和最大间隔，避免了对优化问题的直接求解，因此可以很好地降低计算代价。并且该方法直接从样本出发，可以很好地体现数据的分布特征，不管数据分布是否均匀都可以适用。给出了基于凸包估计的SVM核选择的模型及实现算法。 -Proposed based on minimizing the estimated generalization error bound of the non-optimal estimation method. Most of the nuclear parameter selection methods are to get the best by minimizing the parameter values, but the computational cost for solving optimization problems is quite large, and can not properly reflect the distribution characteristics of the data. In this paper, the non-optimization technology, by minimizing the generalization error to optimize the nuclear and related parameters, due to the direct calculation of the minimum radius and maximum interval, avoiding the direct solution of the optimization problem, it can very well reduce the computation cost. And that the method directly from the sample one can well reflect the distribution chara