遗传算法和蚂蚁算法结合的一种新算法

用于multivariate时间序列分类，利用了weka机器学习系统（本站可下载）-for multivariate time series classification, the use of machine learning system weka (site available for download)

线性神经网络，BP神经网络，Hopfield神经网格，Elman神经网络，RBF神经网络；在模型应用模块中实现了六种实际应用：RBF网络的船用柴油机故障诊断，BP网络的齿轮箱故障诊断，SOM网络的回热系统故障诊断，BP网络的设备状态分类器，SOM网络的人口比例样本分类，SOM网络的土壤性状样本分类。-Linear neural network, BP neural network, Hopfield neural network, Elman neural network, RBF neural network application modules in the model to achieve practical application of Six: RBF network of marine diesel engine fault diagnosis, BP network gearbox fault diagnosis, SOM network regenerative system fault diagnosis, BP network classifier equipment, SOM network the proportion of the population sample classification, SOM network classification of soil samples.

遗传算法的源程序例子，对于初学者有很大帮助，建议多-Genetic algorithm source code examples are very helpful for beginners, the proposed multi-

灰色预测模型称为CM模型，G为grey的第一个字母，M为model的第一个字母。GM（1，1）表示一阶的，一个变量的微分方程型预测模型。GM（1，1）是一阶单序列的线性动态模型，主要用于时间序列预测。 一、GM（1，1）建模 设有数列 共有 个观察值 对 作累加生成，得到新的数列 灰色理论与模型及在车辆拥有量预测中的应用 灰色神经网络交通事故预测比较 灰色系统(第三版)-projections Gray (No. Third Edition)

本程序实现的功能为建立一分类器,用于进行有监督的分类学习.-the program for the establishment of a functional classification, which is used for supervised classification study.

MATLAb语言的遗传算法工具箱，比较全。-MATLAb language of genetic algorithm toolbox, the entire comparison.

连轧过程控制仿真程序，其中包括用自适应遗传算法进行优化的代码-rolling process control simulation programs, including adaptive genetic algorithm optimized code

Solving Traveling Sales Man Problem by the Algorithm of Simulated Annealing. Src only. 100 free of compile error. Including 2 test cases.-Solving Traveling Sales Man Problem by the Algorithm of Simulated Annealing. Src only. 100 free of compile error. Including 2 test cases.

利用VC实现的贝叶斯分类器的源代码，可以用来分类或识别，很值得收藏-The source code of bayes classfication using VC

Biome是一个c++库，它的目的是个人_基于代理的模拟器（象 Swarm 或EcoSim）。它试图尽可能达到高效并且同时有好的设计-PROJECT is a c library, it is aimed at individual _ Agent-based simulator (like Swarm or EcoSim). It seeks to achieve efficient as possible while it is good design