治疗基于代表点的聚类算法，一个数据挖掘算法…

dv-hop的定位算法，已知网络中几个锚节点就可以计算出网络中其他点的坐标，但这种算法有时由于网络密度的稀疏，可能误差会有一些-dv-hop positioning algorithm, known to the network a few anchor nodes on the network can calculate the coordinates of other points, but this algorithm is sometimes due to the sparse network density may be some errors

This directory contains code implementing the K-means algorithm. Source codemay be found in KMEANS.CPP. Sample data isfound in KM2.DAT. The KMEANSprogram accepts input consisting of vectors and calculates the givennumber of cluster centers using the K-means algorithm. Output isdirected to the screen.

模式识别实例工程的源代码-example source code

用于机器人的识别路程的优化,用与其中，去得很好的结果-For the robot to identify the optimal way to use and which to very good results

这是一个很好的关于BP神经网络的程序,用于两类数据的分类.-This is a very good network of BP procedures for the two types of data classification.

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

BP网络解决异或问题的实例，有初始值和最终结果的显示。本网络结构为三层BP网络，各层神经元个数可变，更改相关#define即可。（注释较详细，主函数中调用的函数和矩阵类都定义在文件function.h中）-BP network to solve XOR problem instance, there are initial values and final results are displayed. The BP network structure for the three-tier network of neurons in the number of floors variable, change the relevant# Define you. (Note more detailed, the main function calls the function and matrices are defined in the document in function.h)

人工智能经典问题TSP问题的C语言实现，内含源程序和调试过程生成的文件-AI classic TSP"s C language, and includes source code debugging process produces files

Backpropagation Network Time-Series Forecasting 源码, 经典的BPN人工神经网络例子源码-Backpropagation Network Time-Series Forecasting source, the classic example of artificial neural network BPN source

遗传算法简称GA(Genetic Algorithm)，在本质上是一种不依赖具体问题的直接搜索方法。遗传算法在模式识别、神经网络、图像处理、机器学习、工业优化控制、自适应控制、生物科学、社会科学等方面都得到应用。在人工智能研究中，现在人们认为“遗传算法、自适应系统、细胞自动机、混沌理论与人工智能一样，都是对今后十年的计算技术有重大影响的关键技术”。-Referred to as genetic algorithm GA (Genetic Algorithm), in essence is a kind of do not rely on specific issues of direct search method. Genetic algorithm in pattern recognition, neural networks, image processing, machine learning, optimization of industrial control, adaptive control, biological sciences, social sciences and so on have been applied. Research in artificial intelligence, now that the " genetic algorithms, adaptive systems, cellular automata, chaos theory and artificial intelligence, are the next ten years of the computing technology have a major impact on the key technology."