breadth priority use of artificial intelligence algorithms to solve eight digita...

解TSP问题的遗传算法C语言程序-solution of TSP genetic algorithm C Programming Language

基于基本遗传算法的函数最优化，C++源代码-Price quilt hanging遗price for dialysis tub cavity算Finally, Yang Zhao ， Pro C++ Daitou Tungsten measurements

本人编写的incremental 随机神经元网络算法，该算法最大的特点是可以保证approximation特性，而且速度快效果不错，可以作为学术上的比较和分析。目前只适合benchmark的regression问题。 具体效果可参考 G.-B. Huang, L. Chen and C.-K. Siew, “Universal Approximation Using Incremental Constructive Feedforward Networks with Random Hidden Nodes”, IEEE Transactions on Neural Networks, vol. 17, no. 4, pp. 879-892, 2006. -I prepared by incremental random neural network algorithm, which is characterized by the largest approximation properties can be guaranteed, and fast good results can be used as an academic comparison and analysis. The current benchmark is only suitable for the regression problem. Specific effects may refer G.-B. Huang, L. Chen and C.-K. Siew,

模式识别中的常用搜索算法中的8数码游戏程序-pattern recognition of commonly used search algorithm of eight digital Games

王小平老师的遗传算法-理论应用与软件实现的源代码（matlab， C）-source codes of the book "Genetic Algorithm" by Wang Xiaoping.

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

A星算法实现最短路径的选择,使用方便，功能完善，是学习人工智能作业中必须完成的一步。-Choose the shortest path by the method of AStar

这是一个feret数据库,对做模式识别的人来说非常有用的库.-液feret 菘, 模 式 识 说 浅玫目.

室内移动机器人定位与导航关键技术研究,新思路-Indoor mobile robot localization and navigation key technology research and new ideas

ADALINE(神经网络 vc＋＋编写的)-ADALINE (neural networks, prepared by vc )