基本遗传学习分类系统，C++源代码

优化算法算例,其中有优化算法的相关例子，供学习使用-Optimization examples, including relevant examples of optimization algorithm for learning to use

利用pso算法训练人工神经网络的源代码。-PSO algorithm for the use of training artificial neural network source code.

把 sequential 有导师学习问题转化为传统的有导师学习问题，是weka机器学习系统（本站可下载）的一个拓展-instructors put sequential learning into traditional learning instructors, weka machine learning system (download site), an expansion

一个简单的用MATLAB写的BP算法源程序。-a simple written in MATLAB BP algorithm source.

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数据挖掘中常常会遇到apriori算法 这是apriori算法的java版-data mining algorithm will often encounter this algorithm is algorithm java version of the algorithm

基于GA的BP改进算法，用遗传算法对BP 神经网络算法进行改进试用过 里面有数据是可以使用的-GA-based improvement of BP algorithm, genetic algorithm with BP neural network algorithm tried there are data that can be used

基因算法（GA） GA 是一种启发式的优化法 （heuristic optimization method）， 它是通过既定的随机搜索进行操作．优化问题的可能的解的集合被认为是 个体（individuals）组成的 人群（population）． 一个个体对它的环境的适应程度由它的 健康度（fitness）表示． -genetic algorithm (GA) GA is a heuristic optimization method (heuristic optimi method. 5), which is established through a random search for the operation. Optimization of the solution may be considered a collection of individuals (individuals) of the crowd (pop ulation). It"s an individual adaptation to the environment by its Health (fitness).

10。《用于最优化的计算智能》，Nirwan Ansali，Edwin Hou着，李军，边肇棋译 清华大学出版社 1999年第一版 本书从讨论组合优化中的基本问题――NP问题入手，系统地讲述了近年来所发展起来的智能最优化的各种技术和方法，其中包括启发式搜索、Hopfield神经网络、模拟退火和随机机、均场退火以及遗传算法等；并在此基础上，通过一些典型的应用问题，如旅行商问题、模式识别中的点模式匹配问题、通信和任务调度等问题进一步阐明以上一些基本方法怎样用来解决这些原来具有NP性质的困难问题。本书是作者在美国新泽西州理工学院多年讲授有关课程的基础上写成的。全书深入浅出，理论联系实际。为帮助学生掌握基本概念，提高学习能动性，各章编写了习题。本书可作为通信、计算机、控制各专业的高年级学生和研究生学习有关课程的教材。它对于广大科研工作者也是一本很有实际价值的参考书。 -10. "Optimal for Computational Intelligence," Nirwan Ansali, with Edwin Hou, Li Jun, Pin Zhaoxing chess translation Tsinghua University Press in 1999 the first book version of combinatorial optimization from the discussion of basic questions-- NP problem start, the system described in recent years to develop the intelligent optimization of the technology and methods, These include heuristic search, Hopfield networks, simulated annealing and random machine, mean field annealing and genetic algorithms; and on this basis and through some typical applications, such as the traveling salesman probl

决策树算法 经典的ID3算法 用于决策树规则学习等等 在规则学习以及分类中有重要的作用-classic decision tree mode for classification and rule learning