This is a study artificial intelligence ant algorithm research documents, to thi...

人工智能的教材啊- Artificial intelligence teaching material

java bayes的bin文件，enjoy it！-java bayes the paper bin, enjoy it!

matlab的GA工具箱与vc混和实现遗传算法的源码-Matlab Toolbox GA vc mixed with Genetic Algorithm FOSS

介绍了神经网络模式识别的基本知识，适合于模式识别领域的人员-it introduces the ABC of the pattern recognation of NN, it is for the people of pattern recognation

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。

遗传算法解决NN逼近任意函数-genetic algorithm to solve arbitrary function approximation NN

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

基于遗传算法的分词论文 基于遗传算法的分词论文-Segmentation Based on Genetic Algorithms PapersSegmentation Based on Genetic Algorithms PapersSegmentation Based on Genetic Algorithms Papers

simple implement of genetic algorithm on cards

bayes network classifier toolbox 贝叶斯网络分类器工具箱的bin文件-bayes network toolbox Bayesian classifier network classifier Toolbox for the paper bin