SOFM neural network c++ Source can be used for remote sensing image classificati...

一个pso的演示程序,非常经典,对初学者来说是非常不错的学习资料!-A demo program PSO, very classic, for beginners is a very good learning materials!

麻省理工开发的免费遗传算法类库GAlib,很好用，我用它实现过一些具体问题的遗传算法。- Hemp province technical development free heredity algorithm class storehouse GAlib, is very easy to use, I use it to realize some concrete questions heredity algorithms.

人工智能8数码问题-artificial intelligence problem

利用遗传算法编写的恐龙路径优化走法！可以根据自己的要求改变恐龙的路径-The use of genetic algorithm to optimize the preparation of the dinosaurs walk the path of law! Requirements can change according to their own path of dinosaurs

Autolife模型是一个能够进行“开放式进化”的人工生命系统。每个Agent模型采用可以变化规则表长度的有限自动机模型建模。一方面Agent可以进行自我繁殖，同时模型中的选择机制没有采用显式的适应度函数而是采用能量消耗的简单模型而自发涌现出来，所以可以认为Agent模型是一个类Tierra系统。然而与Tierra、Avida等数字生命模型不同的是，Autolife模型进行了大大的简化，它界面友好，操作直接。虽然没有给每个Agent装配一个虚拟计算机，但是Agent与环境的耦合则可以看成一个图灵机模型，因此Agent可以通过变异而“任意”的编程序。通过Autolife模型，首先人们可以看到一般的生态系统中共存的现象：生物的大爆炸、大灭绝，Agent进化得越来越聪明；其次，用户可以通过变化不同的食物添加规则探索Agent与环境的关系；最后，如果允许Agent通过播种改变环境自动产生食物，那么组织的涌现就是一种不可避免的结果。Agent构成的组织具有自主运动的特性，还可以进行自我修复，可以说Autolife中的组织是一些真正的“活体”。-Autolife model is to conduct an "open-evolution" artificial life system. Each Agent can be used model changes the rules limited the length of the table automatic machine modeling. One Agent can be self-propagation, model selection mechanism not used Explicit the fitness function instead of using the energy consumption of a simple model to emerge spontaneously, so that the agent can be a model category Tierra system. But with Tierra, Avida digital life model is different Autolife model for greatly simplified its

高手学习人工智能心得体会。想学习人工智能的可以来-master learning artificial intelligence experiences. Want to study artificial intelligence can s

模式识别中isodata的 vc++实现-pattern recognition isodata achieve the vc

粒子群算法工具箱，有DEMO程序，可以对16中常见函数测试，并附有神经元网络的训练算法-Particle swarm optimization toolbox, there are DEMO program, you can test for 16 common functions, together with the training algorithm for neural networks

:一书的配套源程序，结合数据挖掘和机器学习的知识,以java语言实现了具有代表性的各类数据挖掘方法.例如:classifier中的ZeroR.OneR.NaiveBayes.DecisionTable.IBK.C45,还有聚类,数据预处理等-: lt; Lt; Data Mining-- Practical Machine Learning Technology and java achieve gt; Gt; A matching the source, combining data mining and machine learning, the knowledge, java language to a representative of the various types of data mining. For example : the classifier ZeroR . OneR.NaiveBayes.DecisionTable.IBK.C45, clustering, data pretreatment

打开压缩包，其中的word文档中提供了“m个工件分配给m架机床的效益最优化问题，使用一种遗传算法解决。”的整个编程思路和过程分析。望有相关需要的朋友喜欢-open compressed, the word document provided "m m allocated to the workpiece-machine efficiency optimization, the use of a genetic algorithm to solve." The entire programming ideas and process analysis. Expect relevant to the needs of friends like