NetLogo实现双货仿真模型

这是一个非常好用的蚂蚁算法(蚁群算法)模拟程序,很好用噢,快来试试吧-This a very user-friendly ant algorithm (ant colony algorithm) simulation program, easy to use Oh, Come and try!

只是Java版实现的蚁群算法与程序结果演示，是学习和理解蚁群算法的好内容。-Only a Java version of the ant colony algorithm to achieve the results and procedures for the demonstration of learning and understanding better the content of ant colony algorithm.

蚁群算法的实现，使用一个例子验证蚁群算法的有效性。-ant algorithm implementation, use an example to verify the validity of ant colony algorithm.

支撑向量机算法的一种改进算法，是基于增量学习的算法-Support Vector Machine Algorithm an improved algorithm is based on the incremental learning algorithm

对股票走势的仿真，基于agent的设计思路-The trend of the stock simulation, agent-based design ideas

java　象棋源程序，人工智能，搜索引擎-java chess source, artificial intelligence, search engines

本代码用基于steve语言的breve软件编写的，此软件是一种3D人工智能的环境模拟器，可以用来构建AGENT-BASED SYSTEM和模拟机器人行为。本代码实现功能如下：机器人服务模拟。自动取得饮料，递送给客人，客人喝完后，另一种清理机器人处理瓶子并运送垃圾堆。主要为了证明机器人运动中的一种Deliberative设计结构。软件下载地址：http://www.spiderland.org/breve/download.php 打开我上传的文件后，点运行就可以看效果。-The code-based software steve language breve prepared, the artificial intelligence software is a 3D environment simulator can be used to build the AGENT-BASED SYSTEM and robot behavior simulation. Realize this function code is as follows: service robot simulation. Automatically beverages, delivered to the guests, the guests after the finish, another robot cleaning up the bottle and the delivery of garbage treatment. Mainly in order to prove that the movement of a robot design structure Deliberative. Software Download: http://www.spiderland.org/breve/download.php open my uploaded file, you can look at the effect of running.

用人工神经网络实现异或的功能。用反向传播算法（BP）来实现神经网络，正确率可以达到80% -using artificial neural network XOR functions. With back-propagation algorithm (BP) to achieve neural network, can achieve an accuracy rate of 80%

Neural Networks ，8种神经网络，BP，RBF，CPN等通过VC++来实现了！-Neural Networks, 8 Neuro network, BP, RBF, CPN, such as through VC++ To achieve!

基于VC++的遗传算法源码（相当经典），非常可观-Based on VC++ Genetic algorithm source code (very classic), very impressive