mflood

是人工免疫克隆算法的函数优化,经过运行,效果较好(Cloning is the artificial immune algorithm to optimize the function, after running better)

迭代划分三角形网络，包括圆形、方形、圆形有孔、不规则实例(Iterative triangulation network, including circular, square, circular hole, irregular examples)

用粒子群算法来优化RBF神经网络权值，使神经网络有更好的非线性函数逼近能力(Using particle swarm optimization to optimize the RBF neural network weights, so that neural network has better ability of nonlinear function approximation)

一个简单的小例子，是关于pso与神经网络结合的。希望有用(A simple example is about the combination of PSO and neural network. Hope to be useful)

关于神经网络的PPT，PDF格式，对神经网络进行了详细的说明和总结，是快速学习和理解神经网络理论的捷径。(On Neural Networks PPT, PDF format, the neural network a detailed description and summary, is quick to learn and understand the neural network shortcuts.)

中小型企业网站的一个例子，具备完整的企业网站功能，包括公司介绍，产品介绍，人员介绍等-Small and Medium Enterprises website an example of a complete enterprise Web site features, including company introduction, product introduction, personnel, etc. Introduction

说明：  西瓜视频爬虫，难点主要获取videoid，signature（这个跟今日头条一致）,其他的就是json数据抓包的问题了。(Watermelon video crawler, the main difficulty is to obtain videoid, Signature (which is consistent with today's headline), and the other is the problem of CAPTURING JSON data package.)

基于LVQ神经网络预测的人脸朝向识别的matlab源程序以及数据(LVQ neural network predictions based on face recognition matlab source towards.)

多智能体一致性实现算法,实现最基本的一致性检测(Simulation for multi-agent consensus problems)

提出一种基于改进粒子群动态搜索算法的网络重构方法，算法把初始粒子群按照适应度的大小分为两个互不交叉，且具有不同分工的子群，并进行动态搜索。通过引入了交叉和禁忌思想，减少了解陷入局部最优的可能性．与遗传、禁忌搜索算法重构的结果进行比较，表明本文算法具有更高的搜索效率，更容易找到全局最优解．(：An improved method based on improved particle swarm optimization dynamic search algodthm networkrcconfiguration is presented in this paper．The initial particle swarm is divided into two different subgroups according to the size of fitness，with a division of labour between the different subgroups of dynamic search．Cross thinking and ideological tabu ale ledinto this algorithm to reduce the possibility of local Optimum．Compared with genetic and tabu search algorithm,the results show that the proposed method possesses a hi．gher search efficiency andis easier tO find the global optimum solutions．)