新型模拟退火算法解决TSP优化问题。自能退火。可用于大多数情况下的优化问题。

蚁群算法,蚁群算法原理及其应用中的源代码-Ant algorithm, ant colony algorithm and its application in source code

//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

迁移学习的经典文章，大多为国际顶级会议论文-Transfer of learning classic articles, most of the international top-level Conference Papers

可以自动生成qbf问题实例,但需要给定一些参数.-can produce QBF instance

一个很好的中国象棋源代码 本人机对弈程序采用了多种搜索算法. 本程序还具有悔棋,还原功能,还可以记录走法.-a good source of Chinese chess game machine code, I use a variety of procedures for search algorithm. The procedure also has to repent Mullick, recovery capabilities, but also can be recorded in law.

经典的人工智能问题 - iris数据分析问题。通过设计三层bp神经网络对花朵数据进行分类识别，并达到了很好的效果。-classic AI problem- iris data analysis problems. Three-bp through the design of neural networks classify data flower identification, and to achieve good results.

gmeans-- Clustering with first variation and splitting 文本聚类算法Gmeans ,使用了3种相似度函数,cosine,euclidean ,KL.文本数据使用的是稀疏矩阵形式. -gmeans clustering with first variation and splitting Gmeans,a text clustering algorithm, uses 3 functions,cosine,euclidean and KL in similarity measuring.Text data are described by sparse matrix.

一个用VC实现的高效bp神经网络算法源代码，希望对大家有帮助.-VC realize an efficient use of bp neural network algorithm source code, and they hope to help everyone.

神经网络C程序的第10章-neural network C procedures for the Chapter 10

采用的是康力山等人确定的实验参数。 对于n个城市的旅行商问题，其参数如下： 初始温度：t0=280, 每一个温度下采用固定的迭代次数L=100n, 温度的衰减系数alpha=0.92 算法停止的准则是当相邻两个温度得到的解变化很小时算法停止。-used the Stanozolol Hill were determined by the experimental parameters. N cities for the traveling salesman problem, the parameters are as follows : initial temperature : t0 = 280, each a fixed temperature of the iteration number L = 100n, temperature attenuation coefficient alpha = 0.92 algorithm to stop the criteria when two adjacent the temperature change was very Solution Algorithm stop.