模式识别中的寻路算法：A星算法的实现及简单应用

6。《非数值并行算法――遗传算法》，刘勇等着 科学出版社 1995年第一版 本书系统地叙述了非数值并行算法之一的模拟退火算法的基本原理以及最新进展，同时为了便于读者解决实际问题，书中对具体算法的步骤作了详细介绍。本书共分七章，第一章介绍算法的思想、特点。发展过程和前景。第二章介绍算法的基本理论。第三章讨论算法解连续优化问题。第四章利用算法设计和优化神经网络。第五章介绍在组合优化中的应用。第六章介绍应用遗传程序设计解决程序设计自动化问题。第七章对遗传算法和其它适应性算法进行比较。 本书可供高校有关专业的师生、科研人员、工程技术人员阅读参考。-6. "Non- numerical parallel algorithms-- Genetic Algorithm" Liu Yong waiting 520-531 1995 version of the first book to systematically describe the non- numerical parallel algorithms one count of simulated annealing Law and the basic tenets of the latest progress, in order to help readers solve practical problems, book of the specific algorithm steps in detail. The book is divided into seven chapters, the first chapter describes the idea algorithm, characteristics. The development process and prospects. The second chapter describes the basic algorithm theory. The third chapter discusses Algorithm for continuous optimization problems. Chapter IV using the algorithm design and optimization of neural netw

用BCB编写的Kohonen程序做优雅的网格分布，将任意维的输入数据，简化为二维x，y平面，竞争学习最佳实践。

MCP(最大截问题)的模拟退火算法程序源码-MCP (the largest cut-off issues) of the simulated annealing algorithm program source

本程序实现了多城市的tsp问题（即旅行商问题）的遗传算法-the process of multi-city tsp (ie, the traveling salesman problem) Genetic Algorithm

clementine8.1中文手册经典的数据挖掘软件说明-clementine8.1 Chinese classic manual data mining software Note

he algorithm is equivalent to Infomax by Bell and Sejnowski 1995 [1] using a maximum likelihood formulation. No noise is assumed and the number of observations must equal the number of sources. The BFGS method [2] is used for optimization. The number of independent components are calculated using Bayes Information Criterion [3] (BIC), with PCA for dimension reduction.

改进遗传算法在TSP中的应用!很好用哦!-Improved Genetic Algorithm in TSP application! Good use Oh!

雷英杰的matlab遗传算法工具箱及应用,内有很多实例的编码-LEI Yingjie of Matlab Toolbox and the Genetic Algorithm application, there are many examples of coding

移动机器人运动学mathematica程序-Mobile robot kinematics mathematica program

人工智能的8数码问题的求解-eight digital artificial intelligence problem solving