一个简单的遗传算法C++类

A*算法，迷宫寻路，初步解析A*算法如何在迷宫寻路-Astar

模式识别――原理、方法及应用-pattern recognition-- principles, methods and applications

通过C4.5 的实现可以进行构建决策树 来进行有效的分类-Through the realization of C4.5 decision tree can be constructed to carry out an effective classification

运用遗传算法对交通流进行分配-use of genetic algorithms on traffic flow distribution

利用ICA变换进行人脸检测,是一种新的人脸检测方法-ICA transform the use of face detection, is a new face detection method

双向广度优先搜索算法法见8SM2.cpp文件，vc6.0环境运行实现-two-way breadth- first search algorithm see 8SM2.cpp France, achieving operating environment vc6.0

模拟蜜蜂采蜜的具有人工生命特性的VB程序 可以作为学习人工生命的一个不错的入门-simulation honey bees with artificial life characteristics of VB program can be used as learning artificial life a good entry

一类球型分布问题的实现-a ball-type distribution of achievement

MATLAB环境下的遗传算法源程序代码压缩包-MATLAB environment genetic algorithm source code package

微分进化算法DE是1995年由Rainer Storn和Kenneth Price首先提出。DE已被证明在求解过程中具有高效性、收敛性、鲁棒性等优点[5,6] 。它在许多优化问题中都表现出优于自适应模拟退火算法、POS 算法、GA算法的性能。DE利用实数值参数向量作为每一代的种群，它的自参考种群繁殖方案与其他优化算法不同。-DE was first proposed in 1995 by Rainer Storn and Kenneth Price and had been proven that it is efficient, convergent, and robust in the solution process. [5,6] In many optimize questions, its performance surpasses the adaptive simulated annealing algorithm, the POS algorithm, and the GA algorithm. DE gets each generation of population using the real value parameter vector, and the crucial idea of DE is a scheme for generating trial parameter vectors.