人工智能bp算法程序以及实验报告

手写汉字识别 应用SVM和神经网络进行识别,可自行训练-Handwritten Chinese Character Recognition Application of SVM and neural networks to identify their own training

基于VB开发的粒子群优化算法的软件及源程序。-VB on the development of particle swarm optimization software and source code.

介绍了神经 网络中的ADALINE算法的C语言实现.-Introduction of the ADALINE neural network algorithm in C language.

用于程序优化与遗传算法-procedures for optimization and genetic algorithms

自适应变步长定向变异遗传算法解函数优化问题 需要调用GAOT5.-Adaptive Variable step directional variation of genetic algorithm optimization solutions function call GAOT5 needs.

研究基于遗传编程的可持续性进化算法的理论与方法，并建立了该算法的数学模型及运算流程.HFC算法实现源代码.-Research based on genetic programming evolutionary algorithm for the sustainability of the theory and method, and set up a mathematical model of the algorithm and the computation flow. HFC algorithm source code implementation.

数据挖掘中常常会遇到apriori算法 这是apriori算法的java版-data mining algorithm will often encounter this algorithm is algorithm java version of the algorithm

这是一个用遗传算法对KDDCUP数据集，实现自动检测的C程序，希望有用。-This is a genetic algorithm with KDDCUP data sets, to achieve automatic detection of the C program, I hope useful.

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

实现了一个简单的花朵进化的模拟过程。 花朵的种群数量是10，共进化了50代。 -The realization of a simple simulation of the evolution of flowers. Flower populations is 10, a total of 50 on behalf of evolution.