模拟3G环境，测试可伸缩视频码流，适合JSVM开发者

收集的关于遗传算法的模糊搜索的ppt资料，有兴趣的可以研究一下-Collected on the genetic algorithm ppt fuzzy search information, interested can look at

此文档是遗传算法原理加源代码。 生物的进化是一个奇妙的优化过程，它通过选择淘汰，突然变异，基因遗传等规律产生适应环境变化的优良物种。遗传算法是根据生物进化思想而启发得出的一种全局优化算法。 -This document is the principle of genetic algorithm source code increases. Biological evolution is a wonderful optimization process, it eliminated by choosing a sudden variation of genetic and other changes in the law to adapt to the environment arising from the fine species. Genetic algorithm is based on ideas of biological evolution and the inspiration derived from a global optimization algorithm.

Using Simulated annealing to solve TSP

用蚁群算法求解TSP（旅行商）问题，按照TSP.m中要求的格式输入程序参数即可运行！-Using Ant Colony Algorithm for TSP (traveling salesman) problems, in accordance with the format requested TSP.m input process parameters to run!

蚁群算法,蚁群算法原理及其应用中的源代码-Ant algorithm, ant colony algorithm and its application in source code

Adaptive Resonance Theory Brain Modeling 人工智能人工神经网络源码-Adaptive Resonance Theory Brain Modeling artificial neural network artificial intelligence source

微粒群算法与其它进化类算法相类似，也采用“群体”与“进化”的概念，同样也是依据个体（微粒）的适应值大小进行操作。所不同的是，微粒群算法不像其它进化算法那样对于个体使用进化算子，而是将每个个体看作是在n维搜索空间中的一个没有重量和体积的微粒，并在搜索空间中以一定的速度飞行。-Particle swarm optimization algorithm with other similar type of evolution, but also the use of " groups" and " evolution" concept is also based on the individual (particle) size of the operation of fitness. The difference is that unlike other particle swarm optimization evolutionary algorithm as the use of evolution for the individual operator, but as each individual in the n-dimensional search space of a weight and size of the particles, and in the search space the speed of a certain flight.

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

测试无约束优化定理求解最小值,包括测试数据,在VC下可以实现,已经调试成功.-test unconstrained optimization for minimum theorem, including test data, the VC can be achieved, debugging has been successful.

Tutorial On Fuzzy Logic