Genetic algorithm source code examples are very helpful for beginners, the propo...

Collection of 30+ AI Neural Network java applets with documentation.

10。《用于最优化的计算智能》，Nirwan Ansali，Edwin Hou着，李军，边肇棋译 清华大学出版社 1999年第一版 本书从讨论组合优化中的基本问题――NP问题入手，系统地讲述了近年来所发展起来的智能最优化的各种技术和方法，其中包括启发式搜索、Hopfield神经网络、模拟退火和随机机、均场退火以及遗传算法等；并在此基础上，通过一些典型的应用问题，如旅行商问题、模式识别中的点模式匹配问题、通信和任务调度等问题进一步阐明以上一些基本方法怎样用来解决这些原来具有NP性质的困难问题。本书是作者在美国新泽西州理工学院多年讲授有关课程的基础上写成的。全书深入浅出，理论联系实际。为帮助学生掌握基本概念，提高学习能动性，各章编写了习题。本书可作为通信、计算机、控制各专业的高年级学生和研究生学习有关课程的教材。它对于广大科研工作者也是一本很有实际价值的参考书。 -10. "Optimal for Computational Intelligence," Nirwan Ansali, with Edwin Hou, Li Jun, Pin Zhaoxing chess translation Tsinghua University Press in 1999 the first book version of combinatorial optimization from the discussion of basic questions-- NP problem start, the system described in recent years to develop the intelligent optimization of the technology and methods, These include heuristic search, Hopfield networks, simulated annealing and random machine, mean field annealing and genetic algorithms; and on this basis and through some typical applications, such as the traveling salesman probl

基本遗传算法 里面的函数可自行更换 适合初学者 容易理解-A function of the basic genetic algorithm which can be suitable for beginners is easy to understand on their own replacement

图像检测模板匹配的Visual C++代码-Image Detection template matching Visual C code

一个完整BP神经网络源代码，包括数据和说明文档,很有用的。-A complete BP neural network source code, including data and documentation, very useful.

遗传算法优化程序-genetic algorithm optimization procedures

面试老鼠和猫连动问题的集中解决方案 可以建议应付面试问题-interview rats and cats even move the concentrated solution can meet the proposed interview questions

人工智能人工神经网络源码，很不错的！！可以学习-Artificial intelligence artificial neural network source code, it is good! ! Can learn

一本不错的与神经网络相关的英文教材。介绍了多种神经网络算法及针对每种算法弱点的改进算法。-A good correlation with the neural network of the English teaching materials

根据粒子群算法的特点，用vc写出了源程序，可以实现粒子群的优化-According to the characteristics of particle swarm optimization, using vc wrote source code, you can achieve the particle swarm optimization