模糊数学与人工智能技术

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

遗传算法与工程设计-Genetic Algorithms and Engineering Design

BP神经网络的C语言实现，对理解神经网络很有帮助。-BP neural network to achieve the C language, very helpful in understanding the neural network.

基于svm的机器学习文本分类方法，具有很好的借鉴意义-Svm-based machine learning text classification methods, with a good reference

基于C语言人工免疫源程序,包括二进制编码的简单遗传算法源程序，二进制编码的简单克隆选择算法源程序-Artificial Immune-based C language source code, including a simple binary-coded genetic algorithm source code, binary-coded clonal selection algorithm simple source

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-TSP problem with a simple test routine, applications good results can be used as a reference for beginners

Fuzzy logic controller that uses mamdani logic.

计算机模式识别技术-the technology of the computer pattern recognation

本程序利用遗传算法实现PID参数的优化问题.-This procedure using genetic algorithm optimization of PID parameters.

weka 的决策树的实现,对数据挖掘感兴趣的可以下哦,很好的呀-if you like Dataming