神经网络与遗传算法在水科学领域的应用…

一种新的ica算法，主要是应用与盲分离算法，大家可以-ica a new algorithm, and are primarily used to blind separation algorithm, we can s

Lin-Kernighan的R-Opt算法。主要思想是CLK，小规模的TSP可以在很短的时间内都到最优解。-Lin-Kernighan algorithm for the R-Opt. The main idea is CLK, small-scale TSP can be in a very short period of time have gone to the optimal solution.

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

该系统使用极其简便，即使 你对各种网络模型不是很深刻的了解，也可以很好的使用该系统。使用时， 你可以自己修改网络的各种参数，交互性较好，而且该系统通过大量的图示 及参数设置，可以让你了解每个应用实例实现的过程及详细步骤。-The system is extremely easy to use, even if you have to various network model is not very profound understanding can be a good use of the system. When used, you can change the network"s own parameters, interactive better, but the system through a lot of icon and parameter settings, so you can understand each application process and the realization of detailed steps.

很好的神经网络教程，里面包含源代码，可以进行相关的修改!-Good neural network tutorial, which contains the source code, can be related to changes!

免疫算法求解函数优化问题运行时请选择所要的函数,并且点Button1执行-immune function algorithm optimization runtime please select the function and implementation point Button1

清华仿真机器人2002年源码.rar。可以从下面这个网址找到更详细的内容。 http://www.lits.tsinghua.edu.cn/robocup-Qinghua robot simulation source code in 2002. Rar. From below the site to find more details. Http://www.lits.tsinghua.edu.cn/robocup

极小化误差平方和算法聚类源代码，下载后直接运行就可以了-Minimizing the error sum of squares clustering algorithm source code can be run directly after downloading the

matlab所有的工具箱，包括统计工具箱、拟合工具箱、微分方程工具箱、遗传算法工具箱、模拟退火工具箱、优化工具箱。随机数工具箱、等等。很全面-All matlab toolbox, including statistical toolbox, fitting toolbox, toolbox differential equations, genetic algorithm toolbox, simulated annealing Toolbox, Optimization Toolbox. Random number toolbox, and so on. Very comprehensive

该程序是基于BP网络的PID控制系统。系统由两部分构成：经典的PID控制器和神经网络。-that the procedure was based on BP network PID control system. System consists of two parts : the classic PID controller and neural networks.