他算法相当于Infomax贝尔和Sejnowski 1995 [ 1 ]利用最大。

Lin-Kernighan heuristic for the TSP and minimum weight perfect matching

用VC++实现的BP（反向传播负反馈）神经网络算法-with VC BP (BP negative feedback) neural network algorithm

pso 的一个演示源码，欢迎初学者下载，共同进步-pso source of a presentation, please download beginners, and common progress! ! ! ! ! !

本人用matlab内部函数编写的BP神经网络算法实现，采用目前最先进和流行的LV算法，速度很快，效果很好-I use the internal function matlab prepared BP neural network algorithm, using the most advanced and popular LV algorithm, fast, good effect

flex在线股票系统源代码，是非常实用的一款程序-flex-line stock system source code, is a very useful program

蚁群算法：用来进行路径设计、查找、规划等-Ant Colony Algorithm: Path used for design, search, planning, etc.

6。《非数值并行算法――遗传算法》，刘勇等着 科学出版社 1995年第一版 本书系统地叙述了非数值并行算法之一的模拟退火算法的基本原理以及最新进展，同时为了便于读者解决实际问题，书中对具体算法的步骤作了详细介绍。本书共分七章，第一章介绍算法的思想、特点。发展过程和前景。第二章介绍算法的基本理论。第三章讨论算法解连续优化问题。第四章利用算法设计和优化神经网络。第五章介绍在组合优化中的应用。第六章介绍应用遗传程序设计解决程序设计自动化问题。第七章对遗传算法和其它适应性算法进行比较。 本书可供高校有关专业的师生、科研人员、工程技术人员阅读参考。-6. "Non- numerical parallel algorithms-- Genetic Algorithm" Liu Yong waiting 520-531 1995 version of the first book to systematically describe the non- numerical parallel algorithms one count of simulated annealing Law and the basic tenets of the latest progress, in order to help readers solve practical problems, book of the specific algorithm steps in detail. The book is divided into seven chapters, the first chapter describes the idea algorithm, characteristics. The development process and prospects. The second chapter describes the basic algorithm theory. The third chapter discusses Algorithm for continuous optimization problems. Chapter IV using the algorithm design and optimization of neural netw

离散二进制粒子群算法 DPSO -DPSO

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

基因算法（GA） GA 是一种启发式的优化法 （heuristic optimization method）， 它是通过既定的随机搜索进行操作．优化问题的可能的解的集合被认为是 个体（individuals）组成的 人群（population）． 一个个体对它的环境的适应程度由它的 健康度（fitness）表示． -genetic algorithm (GA) GA is a heuristic optimization method (heuristic optimi method. 5), which is established through a random search for the operation. Optimization of the solution may be considered a collection of individuals (individuals) of the crowd (pop ulation). It"s an individual adaptation to the environment by its Health (fitness).