基于遗传算法实现的人工控制的登月工程的模拟程序

Boltzmann Machine Optimization 人工智能人工神经网络源码-Boltzmann Machine Optimization of artificial neural network artificial intelligence source

分类算法的研究很详细 很权威的 值得看看 有研究意义-Classification algorithm in detail to see if there should be a very authoritative research significance

Code for Truth Maintenance System in Artificial Intelligence.-Code for Truth Maintenance System in Artificial Intelligence.

遗传算法的c语言程序-Genetic Algorithm c Language Program

以黎曼几何为理论依据，基于S.Amari的修正核函数思想提出了两种新的保角变换，用其对核函数进行数据依赖性改进，进一步提高支持向量机分类器泛化能力。以人工非线性分类问题 为对象进行研究，仿真实验结果表明采用新保角映射可以快速显著地改善分类器泛化性能，而且能大幅度地减少支持向量的数目。-Two novel conformal transformations were proposed based on the Riemannian geometry theory and S.Amari’sidea.And the kernel function was modified by the transformation in a data-dependent way.Our experimental results for theartificial nonlinear data set show that the generalization performance of support vector machines classifier is improvedremarkably and the number of support vectors is decreased greatly.

Aprior算法实现程序-Aprior algorithm program! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! !

佐治亚理工学院的人工智能平台。由Java编写。仅供学习人工智能的网友学习。-Georgia Institute of Technology" s artificial intelligence platform. By Java. User to study artificial intelligence to learn only.

MCRGSA------组播路由问题遗传模拟退火算法 ％M-----------遗传算法进化代数 ％N-----------种群规模，取偶数 ％Pm----------变异概率调节参数 ％K-----------同一温度下状态跳转次数 ％t0----------初始温度 ％alpha-------降温系数 ％beta--------浓度均衡系数 ％ROUTES------备选路径集 ％Num---------到各节点的备选路径数目 ％Cost--------费用邻接矩阵 ％Source------源节点标号 ％End---------目的节点标号组成的向量 ％MBR---------各代最优路径编码-MCRGSA------ Multicast Routing genetic simulated annealing% M----------- genetic algorithm algebra% N----------- population size, even take Pm----------% probability parameter variation%----------- same temperature K Jump under a number of state----------% t0 initial temperature cooling% alpha------- beta coefficient%-------- balanced concentration coefficient% ROUTES------ Alternative Path Set% Enable--------- nodes to the number of alternative paths%-------- Cost adjacent costs Matrix% Source------ source node labeling% End--------- destination node labeling Group Vector%% of the MBR--------- generations optimal path coding

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

高斯混合模型算法-Gaussian mixture model algorithm