association rules of frequent item sets Algorithm trillion*, a very good algorit...

ArcObject的空间查询代码，比较简单和初步的供大家一起学习-The spatial query ArcObject code is relatively simple and everyone together for a preliminary study

详细介绍了SVM 和RVM的区别及各自的优点，说明RVM在很多方面优于SVM-Described in detail the difference between SVM and the RVM and their respective advantages, indicating RVM in many ways superior to SVM

模式识别分类 内有聚类算法.分段线性算法-Categorization of pattern recongnization includes clustering algorithm and segmentation linear algorithm.

神经网络模式识别及其实现，第10章 内含：ART 和VQ 算法。 终于上传完，本来想一次性发上来的，但结果失败了，只好一个一个发。-pattern recognition and neural network to achieve, Chapter 10 consisting of : ART algorithm and VQ. Finally upload End, originally wanted onto a one-time, but the result of the failure, but a one-fat.

关于细胞自动机的例子，希望有志于这领域的同仁研究-on Cellular Automata example, are interested in this area of research colleagues! !

Hopfield 网――擅长于联想记忆与解迷路 实现H网联想记忆的关键，是使被记忆的模式样本对应网络能量函数的极小值。 设有M个N维记忆模式，通过对网络N个神经元之间连接权 wij 和N个输出阈值θj的设计，使得: 这M个记忆模式所对应的网络状态正好是网络能量函数的M个极小值。 比较困难，目前还没有一个适应任意形式的记忆模式的有效、通用的设计方法。 H网的算法 1）学习模式――决定权重 想要记忆的模式，用-1和1的2值表示 模式：-1，-1，1，-1，1，1，... 一般表示： 则任意两个神经元j、i间的权重： wij=∑ap(i)ap(j)，p=1…p； P：模式的总数 ap(s)：第p个模式的第s个要素（-1或1） wij：第j个神经元与第i个神经元间的权重 i = j时，wij=0，即各神经元的输出不直接返回自身。 2)想起模式： 神经元输出值的初始化 想起时，一般是未知的输入。设xi(0)为未知模式的第i个要素（-1或1） 将xi(0)作为相对应的神经元的初始值，其中，0意味t=0。 反复部分：对各神经元，计算： xi (t+1) = f (∑wijxj（t）-θi), j=1…n, j≠i n―神经元总数 f（）--Sgn（） θi―神经元i发火阈值 反复进行，直到各个神经元的输出不再变化。-Hopfield network-- good at associative memory solution with the realization of lost H associative memory networks, are key to bringing the memory model samples corresponding network energy function of the minimum. With M-N-dimensional memory model, the network N neurons connect between right wij and N output threshold j design makes : M-mode memory corresponding to the network is a state network energy function is the M-000 minimum. Mor

用Prolog求解传教士和野人问题 复习经典谓词演算中的归结原理，掌握人工智能程序设计语言Prolog，理解通过搜索求解问题实现人工智能的思想。-Using Prolog to solve the issue of missionaries and Savage Classical Predicate Calculus review summarized in principle, grasp the artificial intelligence programming language Prolog, to understand to solve problems by searching for the realization of the idea of artificial intelligence.

遗传算法求解函数极值，一个基础的实用程序-Extremal function of genetic algorithm, one based on utility

matlab神经网络应用设计，里面随有详细代码-Matlab neural network application design, which with a detailed code

遗传算法 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 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."