Matlab遗传算法工具箱函数及应用实例 Matlab遗传算法工具箱函数及应用实例...

CPN算法的matlab实现，CPN人工神经网络-Matlab algorithm of network，The artificial neural network, network

高性能交流伺服系统及其复合控制策略研究，浙江大学博士论文。 关键词:交流伺服系统，矢量控制，直接转矩控制，复合控制，PID控制，GA，IGA，模糊控制，切换控制，协调控制-High Performance AC Servo System and its Advanced Mixed Practical Control Strategy.Thesis of Zhejiang University. Keywords:AC servo system, Vector Control, Direct Torque Control,Combined Control, PID Control, GA, IGA, Fuzzy Control, Coordinating Control.

介绍了神经 网络中的CPN算法的C语言实现.-Introduce a neural network algorithm in C language CPN realize.

模式识别与人工智能，圆检测HOUGH变换的改进算法-Pattern Recognition and Artificial Intelligence, HOUGH transform circle detection algorithm to improve

经典的人工智能问题 - iris数据分析问题。通过设计三层bp神经网络对花朵数据进行分类识别，并达到了很好的效果。-classic AI problem- iris data analysis problems. Three-bp through the design of neural networks classify data flower identification, and to achieve good results.

主要实现了烧结矿碱度的神经网络预测，训练精度高-The main achievement of the sinter basicity of the neural network prediction, training and high precision

本书就使用matlab实现bp神经网络进行了较为详细的说明，书中包含许多具体的实例说明，希望能为大家带来一定的帮助。-book on the use of Matlab bp neural network to achieve a more detailed description of the book contains many specific examples, we hope to bring help to a certain extent.

人工智能中经典算法-宽度搜索和启发是搜索（A*算法）在VC环境下的实现代码，对于学习人工智能有很多帮助- In the artificial intelligence the classical algorithm- width search and the inspiration are the search (the A* algorithm) under the VC environment realization code, has regarding the study artificial intelligence very helps

极小化误差平方和算法聚类源代码，下载后直接运行就可以了-Minimizing the error sum of squares clustering algorithm source code can be run directly after downloading the

vb写的改进的遗传算法程序。是一些通用代码，与具体问题对应的代码空出来，用的时候填进去。根据我的经验，要想用好遗传算法，代码必须自己写，因为问题不同，编码，杂交，变异算子可能都不一样。特别是杂交算子，需要根据问题调整，甚至创造出新的杂交方法。而且适应度计算的代码也需要自己写，特别是带约束的优化问题 -vb write improvement in the genetic algorithm. Some common code, with the specific issues the corresponding code space, and the time spent filling into account. According to my experience, in order to make good use of genetic algorithms, code must write their own, because different issues, coding, hybridization and mutation operator may not like. In particular hybrid operator, the need to adjust the problem, or even create a new hybrid method. But fitness calculation of the code required to write their own, especially with the constrained optimization problem