simulated annealing and genetic algorithms hybrid vehicle routing problem solvin...

LMS-Newton自适应算法源码 反正结果刻与LMS算法相比较，显示了较好的性能。-LMS-Newton adaptive algorithm source code in any case engraved with the LMS algorithm results compared, showing a better performance.

该程序介绍了一种简单的遗传算法应用程序，采用matlab高效编程，适合于二进制编码的典型应用。-The program introduced a simple application of genetic algorithm using matlab efficient programming, suitable for the typical application binary code.

停车诱导系统中车位预测模型的研究 摘 要 研究城市停车诱导系统的停车车位占有率预测问题。首先提出墓于B P神经网络的车位占有预测模型， 同时将自适应 学习速率调整法和加入动量项方法用于改善基本B P神经网络， 优化了学习速率， 减少了训练过程的震荡趋势， 改善了网络的收效 隆。以此为基础实现了停车位的智能预测 0最后， 进行了多种方法比对实验-err

用Ｃ语言实现的神经网络，采用遗传算法对网络进行训练，有很快的收敛速度！-C language of neural networks, genetic algorithm was used to train the network, the speed of convergence very soon!

关于粒子群优化算法的实现.使用java语言实现。-On the Particle Swarm Optimization Algorithm. Using java language.

一个自主机器人的电力传输线检查可引起电压的输电线路作为电源来源提出。该机器人采用电流互感器的主要促使目前从输电线路和远见功能浏览。结果表明，该机器人可以 自动沿着输电线路。-An autonomous robot for the power transmission line inspection that can induce the voltage from the transmission line as a power source is presented. The robot uses current transformer principal to induce the current from power transmission line and vision function to navigate. The results have shown that the robot can automatically move along the power transmission line.

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.

用BP神经网络进行对啤酒质量的识别，各个参数可以自己进行修改。-Using BP neural network to identify the quality of beer, all parameters can be modified.

//开发平台：Microsoft .NET Framework 2.0，Microsoft Visual C# 2005 Express //日期：2005.3.12 //作者：刘波 //粒子群优化算法(PSO)：本算法求目标函数的最小值-//development platforms : Microsoft.NET Framework 2.0, Microsoft Visual C# 2005 Express// Date : 2005.3.12// Author : Liu Bo// Particle Swarm Optimization (PSO) : The algorithm for the minimum objective function

产品设计时间智能预测方法的研究，值得借鉴一下-product design time intelligent prediction method of research, worth learning about