TSP问题的一个简单实验例程,应用效果不错,可以作为初学者的参考...

是各种常用算法的集合，又递归、神经网络、遗传、枚举、排序、圆周率求解等等。是学习的好材料。-Is a collection of various commonly used algorithms and recursive, neural networks, genetic, enumeration, sorting, solving, etc. pi. Is a good learning materials.

自适应遗传算法matlab代码.自适应遗传算法的问题是很容易早熟,好处就是速度快 .不过我将在其中会引入一个早熟判定标志的，并设定一个阈值，如此以来，就可以防止早熟现象了 -Adaptive genetic algorithm Matlab code. Adaptive genetic algorithm is very easy precocious, advantage is faster. However, in which I will be introducing an early sign of determination, and set a threshold, so, you can prevent precocious phenomenon

这是用C语言编写的ID3算法，希望对大家有所帮助-This is the C language prepared by the ID3 algorithm, we hope to help

使用java构建神经网络的开源项目教程，是java爱好者学习神经网络的难得教材。虽然是英文教材，但是语言简单，易懂。书中前几章对于神经网络基本原理的讲解十分通俗易懂，利于初学者对相关知识的理解和吸收，即使不是java编程者，也可以从中受益匪浅。 -Using the java open source project to build neural networks tutorial java lovers are rare neural network learning materials. Although the materials are in English, but the language simple, easy to understand. The book for the first few chapters explain the basic principles of neural networks is very user-friendly, which will help beginners to understand and absorb the relevant knowledge, if not the java programmers can also be benefited from.

介绍了在LabView环境下的神经网络算法-Introduced in the LabView environment, the neural network algorithm

用于求解TSP的蚁群算法，C 语言 已经运行过-Basic Ant Colony Algorithm for TSP

基本遗传算法程序包-basic genetic algorithm program package

height 遗传身高计算 根据父母的升高计算后代身高-height

this demo is to show you how to implement a generic SIR (a.k.a. particle, bootstrap, Monte Carlo) filter to estimate the hidden states of a nonlinear, non-Gaussian state space model.-this demo is to show you how to implement a ge neric SIR (a.k.a. particle, the bootstrap. Monte Carlo) filter to estimate the hidden stat es of a nonlinear. non-Gaussian state space model.

cost存放了一个强连通图的边权矩阵，作为一个实例。 可在workspace中加载 运用此算法要注意多次试验。 bianquan.m文件给出了一个参数实例，可在命令窗口中输入bianquan,得到邻接矩阵C和节点个数N以及一个任意给出的路径R,，回车后再输入jiaohuan3,得到了最优解。 由于没有经过大量的实验，又是近似算法，对于网络比较复杂的情况，可以尝试多运行几次jiaohuan3,看是否能到进一步的优化结果。-storage cost of a strongly connected graph edge weight matrix, as an example. Can be loaded in the workspace to use this algorithm to the attention of numerous tests. bianquan.m document gives examples of a parameter can be in the command window, type bianquan, be the adjacency matrix C and the node number N and an arbitrary given path R,, carriage return after the input jiaohuan3, have been the optimal solution . After the absence of a large number of experiments, it is approximate algorithm, for more complex network situations, you can try to run several jiaohuan3, can look to further optimize the results.