simulated annealing algorithm for TSP

This toolbox contains re-implementations of four different multi-instance learners, i.e. Diverse Density, Citation-kNN, Iterated-discrim APR, and EM-DD. Ensembles of these single multi-instance learners can be built with this toolbox

K-均值聚类算法的编程实现。包括逐点聚类和批处理聚类。K－均值聚类的的时间复杂度是n*k*m，其中n为样本数，k为类别数，m为样本维数。这个时间复杂度是相当客观的。因为如果用每秒10亿次的计算机对50个样本采用穷举法分两类，寻找最优，列举一遍约66.7天，分成3类，则要约3500万年。针对算法局部最优的缺点，本人正在编制模拟退火程序进行改进。希望及早奉给大家，倾听高手教诲。-K-means clustering algorithm programming. Point by point, including clustering and clustering batch. K-means clustering of the time complexity of n* k* m, n samples, several types of k, m sample dimension. The time complexity is a very objective. Because if we use one billion times per second the computer using 50 samples of two exhaustive method to find the optimal set out again about 66.7 days, divided into three categories, offering 3,500 years. Local optimal algorithm against the shortcomings, I was prepared simulated annealing process improvements. Early Feng hope for everyone, listen to the master teachings.

用模拟退火法高效的计算图论中哈密顿贿赂的最短路径-simulated annealing method of calculating efficient graph theory Hamiltonian bribery Shortest Path

遗传算法和神经网络结合，利用两种算法的优点，有很好的参考价值-Genetic algorithms and neural networks combine the advantages of using two algorithms, a very good reference value

神经网络训练程序，用来进行RBF网络的权值训练，利用训练好的权值可以进行自适应滤波！-neural network training procedures used for RBF network weights training. good use of training weights can be adaptive filtering!

我根据书上算法自编的蚁群程序，也是我的中期筛选设计。目录下函数收敛图是用了VC的结果，在matlab里画的-algorithm based on the book written by Ant procedures, and also my mid-screening design. Directory function convergence plan is the result of the VC in Matlab Lane painting

基于梯度法编写的RBF神经网络程序，实现对输入数据的逼近-Gradient method based on the preparation process of the RBF neural network to achieve the approximation of the input data

我收集整理的有关于系统辨识的资料和一些方法的优缺点-I have collated the information on the system identification and the advantages and disadvantages of some methods

用于数据挖掘的分类算法,基于c语言的,一个c4.5分类算法-used for the classification of data mining algorithms, based on the c language, a classification algorithm c4.5

本例是本人写的遗传算法的最简单的一个实现，并且带有一个说明文档。用C语言编写，在TurborC中调试，由于当时在随机数产生上没有种种子，所以极易收敛，有兴趣可以种上种子试一下。-the cases I wrote is the most genetic algorithm to achieve a simple, and with a documented. C language, in which TurborC debugging, because the random number generator not all sons, so vulnerable convergence are interested can plant seeds try.