人工智能的一种典型的启发式搜索算法，是一种最好优先的算法，但要加上一些约束条件。...

人工智能小模型，货郎担问题，一个简单的 实例-Artificial intelligence model:a simple instance of goods selling burden problem.

十折交叉验证方法的matlab code 再模式识别中是一个非常重要的试验方法-a very important technique crossvalidate in pattern recognazition

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

Dynamic Programming Code for the TSP

Demonstration and test of the kernel-ica package

CPN能提供强大的分类功能.介绍CPN(Counter Propagation Networks)神经网络的结构、训练及计算的基础上,详细讨论了CPN在离散事件动态系统(DEDS)仿真、仿真优化等方面的应用。 -CPN can provide powerful classification. Introduction CPN (Counter Propagation Networks) neural network structure, training and calculated on the basis of a detailed discussion of the CPN in Discrete Event Dynamic System (DEDS) simulation, simulation optimization applications.

用c语言编写的粒子群算法程序，下载后可以直接使用-With the c language of the particle swarm optimization program, download can be used directly

C＋＋编写的机器学习算法 Lemga is a C++ package which consists of classes for several learning models and generic algorithms for optimizing (training) the models-prepared by the machine learning algorithm Lemga C is a package which con sists of classes for several learning models an d generic algorithms for optimizing (training ) the models

神经网络控制作为一种全新的智能控制方法,是解决非线性系统预测和控制问题的一种重要手段,受到了许多专家学者的广泛关注,是目前国内外研究的热点之一。本文着重研究前向神经网络的学习算法,简单探讨了BP算法在逼近非线性系统中各个因素对系统的影响。 -Neural Network Control as a new intelligent control method is to solve the nonlinear system to predict and control an important means by many experts and scholars in a wide range of concerns, is one of the hot research. This article focuses on feedforward neural network learning algorithm, a simple BP algorithm of approximation of nonlinear systems in the various factors on the system.

围绕粒子群的当前质心对粒子群重新初始化.这样，每个粒子在随后的迭代中将在新的位置带着粒子在上次搜索中获得的“运动惯性”（wvi）向Pi，Pg的方向前进，从而可以在粒子群的运动过程中获得新的位置，增加求得更优解的机会.随着迭代的继续，经过变异的粒子群又将趋向于同一点，当粒子群收敛到一定程度时又进行下一次变异，如此反复，直到迭代结束.-particle swarm around the center of mass of the current PSO reinitialization. Thus, Each particle in the next iteration will be in the new location with particles in the last search was the "inertia" (wvi ) Pi, Pg orientation, and thus can PSO course of the campaign was a new position, increase seek better solutions opportunities. With the continued iteration, after variation of PSO will tend to the same point. When PSO converge to a certain extent when the next variation, so repeatedly, until the end of iteration.