蚂蚁算法，c语言版，其中，‘F’点表示食物，‘H’表示窝，白色块表示障碍物，‘+’就是蚂蚁了。...

用Fast BP实现复杂的函数逼近,对初学者有一定的帮助,是在BP的基础上增加了R.-Fast BP achieved with a complex function approximation, there is some help for beginners, is based on the BP increase in R.

//开发平台：Microsoft .NET Framework 2.0，Microsoft Visual C# 2005 Express //日期：2005.3.12 //作者：刘波 //粒子群优化算法(PSO)：本算法求目标函数的最小值-//development platforms : Microsoft.NET Framework 2.0, Microsoft Visual C# 2005 Express// Date : 2005.3.12// Author : Liu Bo// Particle Swarm Optimization (PSO) : The algorithm for the minimum objective function

手写汉字识别 应用SVM和神经网络进行识别,可自行训练-Handwritten Chinese Character Recognition Application of SVM and neural networks to identify their own training

模拟退火算法 模拟退火算法(Simulated Annealing,简称SA算法)是模拟加热熔化的金属的退火过程，来寻找全局最优解的有效方法之一。 模拟退火的基本思想和步骤如下： 设S＝{s1,s2,…,sn}为所有可能的状态所构成的集合， f：S―R为非负代价函数，即优化问题抽象如下： 寻找s*∈S，使得f(s*)＝min f(si) 任意si∈S （1）给定一较高初始温度T，随机产生初始状态S （2）按一定方式，对当前状态作随机扰动，产生一个新的状态S’ S’＝S＋sign(η).δ 其中δ为给定的步长， η为[－1,1]的随机数-simulated annealing algorithm (Simulated Annealing, or SA algorithm) is a simulation of heating molten metal in the annealing process, to find the global optimum one of the effective ways. Simulated Annealing basic ideas and the steps are as follows : S = (s1, s2, ..., sn) for all possible state posed by the pool, f : S-R non-negative cost function, that is abstract optimization problems are as follows : Find S* s, making f (s*) = min f (si) arbitrary si S (1) to set a higher initial temperature T, randomly generated initial state S (2) of a certain form, the current state of random disturbance, have a new state S "S" = S+ sign (). delta where given for the step, [-1,1] Random Number

C++神经网络开发包,基于C++语言，VisualC++环境-C++ Neural network development package, based on the C++ Language, VisualC++ Environment

为模型参数中的动静比例知道的情况 属于一种新的模型 - The situation knew which for the model parameter in sound of something astir proportion belongs to one kind of new model

三篇蚁群优化算法的硕士论文，介绍详细，解释清楚，是初学者的入门指导。-3 Ant Colony Optimization Algorithm for master

matlab程序计算经典数学问题：最短路和次短路问题-matlab program calculated the classical mathematical problem: The most short-circuit and sub-shortest path problem

本人编写的GramSchmidt神经网络算法，和传统的神经网络算法比较，该算法能自动产生神经元，节约时间，速度快！ 本人还加了自动产生分类的方法和适合各种函数的转换，该zip包括两个文件，一个是GramSchmidt正交分解，是个子函数，主函数是orth_GramSchmidt，放在同一目录下，就可运行，可以对benchmark的逼近和分类问题提供解决方案-I prepared GramSchmidt neural network algorithm, and the traditional neural network algorithm, the algorithm can automatically generate neurons, saving time, fast! I also added a method of automatically generated classification and conversion for a variety of functions, the zip includes two documents, one is GramSchmidt orthogonal decomposition is a sub-function, the main function is orth_GramSchmidt, on the same directory, you can run can benchmark approximation and classification problems to provide solutions

c语言神经网络程序包-neural network package