资源列表
hundunPSO
- 混沌粒子群处理的经典程序，主要用于学习基本的混沌粒子群算法- end pixbin((2*kk-1):2*kk) = dec2bin( displace(nn2),2)
NNLM1
- 神经网络与机器学习第一章：感知器分类半月形数据-Neural Networks and Machine Learning Chapter I: Classification meniscus sensor data
Tsp
- 用GA算法解决30城市的TSP问题，城市的数量和距离需要手动输入。-30 city TSP problem solving with GA algorithm, the number and distance of the city' s need to manually enter.
C++代码实现了BP网络
- 以下C++代码实现了BP网络，通过8个3位二进制样本对应一个期望输出，训练BP网络，最后训练好的网络可以将输入的三位二进制数对应输出一位十进制数。-The following C++ code to achieve the BP network, by eight 3-bit binary sample corresponds to a desired output, BP network training, the last three binary input trained network
StatLSSVM
- 支持向量机工具箱By Kris De Brabanter,标准的非参数回归，健壮的回归，一些调优标准等经典交叉验证，较好的交互性-The StatLSSVM toolbox is written so that only a few lines of code are necessary in order to perform standard nonparametric regression, regression with correlated errors and robust regre
BP-perdict
- BP神经网络用于风功率预测，可以仿真出风功率以及每个点的误差-BP neural network is used to predict wind power, wind power can be simulated and error for each point
huafenlei
- 使用BP神经网络，进行花朵分类，BP网络学习基础-Use BP neural network for classification flowers, BP network learning foundation
SA_solve_TSP
- 模拟退火算法解决旅行商问题，操作步骤详见readme.txt-Simulated annealing algorithm to solve the traveling salesman problem, the steps described in Readme.txt
backtracking_solve_sudoku
- 回溯法解决数独问题，文件读取数独游戏，空位使用0补齐，输出为填充完毕的数独-Backtracking to solve Sudoku problems, file reads Sudoku, use 0 vacancies filled, the number of output is only completed filling
A_star_solve_Eight_digital
- A*算法解决八数码问题，文件读取八数码，输出为操作步骤。-A* algorithm to solve eight digital, file reads eight digital outputs for the steps.
GA_solve_TSP
- 遗传算法解决旅行商问题，文件读入城市数量，城市名称，坐标。输出为最短路径的城市序列以及路径距离。-Genetic algorithm to solve the traveling salesman problem, read the file into the number of cities, city name, coordinates. Output sequence for the city as well as the shortest route the route.
Naive_Bayesian_classify_version
- 朴素贝耶稣算法进行文本分类，删除“无用词”，对训练集训练之后完成对测试集的测试，并输出测试集文档属于哪个分类-Tony simple algorithm for text classification Jesus, delete " without words" , after training set for the completion of the test set of tests and test sets the output document belongs Cat