遗传算法NSGA2算法解决多

连续型粒子群算法的java实现，可以自己设计粒子群算法（继承Swarm和Particle类），包含有三个个抽象类（Swarm、Particle、Problem），可以继承Problem类自定义新的问题。-continuous particle swarm algorithm to achieve the java can design their own PSO algorithm (inheritance and Particle Swarm), contains an abstract category 3 (Swarm, Particle, Problem), can be inherited from the definition of Class Problem new problems.

利用c语言实现人工智能神经元网络的hopfield算法-Use c language to achieve artificial intelligence neural network algorithm hopfield

MATHEMATICA 软件运用 The biggest similarity for tsp-MATHEMATICA software to use The biggest similarity for tsp

对模式识别中的字符串模板匹配问题进行的研究，设计了对任意字符串进行匹配和字符串相似度，即列文斯顿距离进行计算的算法-right pattern recognition template matching string for the research and design of the arbitrary strings and string matching similarity, Ken Livingstone distance calculation algorithm

这是一本粗糙集数据挖掘的书，其中同时介绍了其他几种数据挖掘方法，并进行了相关对比-This is a rough set data mining of the book, which also introduced several other data mining methods, and conduct the relevant comparison

人脸检测源代码,是人工智能检索方面比较常用的,大家下班啊-Face Detection source code, artificial intelligence search area is relatively common, we work ah

SVM的一个源程序，功能很强大，实现的结构很巧妙-SVM as a source, function is very powerful and realize the structure is a clever

人脸检测代码示例系统.rar 希望对大家有所启发。-Face Detection System code examples. Rar we hope to inspire.

The software implements particle filtering and Rao Blackwellised particle filtering for conditionally Gaussian Models. The RB algorithm can be interpreted as an efficient stochastic mixture of Kalman filters. The software also includes efficient state-of-the-art resampling routines. These are generic and suitable for any application.-The software implements particle filteri Vi and Rao Blackwellised particle filtering az r conditionally Gaussian Models. The RB algori thm can be interpreted as an efficient stochast ic mixture of Kalman filters. The software also includes efficient state-of-the-art resampl ing routines. These are generic and suitable az r any application.

基于matlab的改进模拟退火算法（经典）-Matlab-based improvements in simulated annealing algorithm (classical)