genetic algorithm to achieve (reproduced)

基于遗传算法的排课系统，可以实现多种课程的排列-based on genetic algorithm Course Scheduling System, can achieve a wide variety of courses with the

WEKA 3-5-5 Explorer 用户指南 原中文版-Explorer how to use weka 2-5-5

利用pso算法训练人工神经网络的源代码。-PSO algorithm for the use of training artificial neural network source code.

数据挖掘中dbscan算法的vc实现的源代码-Source code of DBSCAN algorathm of data mining with VC

解非线性规划模型的遗传算法，用c++语言编写，注释完整，结构清晰-Genetic Algorithm for nonlinear programming

径向基函数网络应用实例-RBF Network Application

一种汉字模式识别的VC++源代码，里面包含了学习与识别的算法实现，识别一种汉字前，先学习几遍。识别率高，对学习与研究模式识别很有好处。方便修改。-a Chinese character pattern recognition VC source code, which contains the learning and recognition algorithm, a Chinese character recognition, first learn several times. The high recognition rate for the study and research of pattern recognition is very good. To facilitate change.

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

一个好用的数据挖掘算法，有感兴趣的朋友常联系了。-a user-friendly data mining algorithms, often friends interested in the link.

遗传算法中的NSGA2算法实现，解决多目标遗传算法求解Pareto近似解，具有很好的运行效果-Genetic Algorithms NSGA2 algorithm to solve multi-objective Pareto genetic algorithm approximate solution, with very good operating results