资源列表
RouletteWheelSelection
- GA 算法中 一种选中算法selection(Based on Roulette wheel selection input is an array of any real number values)
account
- good to use for control simulation
新建文本文档.zip
- KNN分类是一个懒惰的分类方法，以K为值，根据距离公式的一种分类方法(KNN classification is a lazy classification method, taking K as a value, and a classification method based on distance formula)
单纯形法
- 解决线性规划问题的单纯形法，使用linprog函数多约束问题(A simplex method for solving linear programming problems)
BP1
- 拟合函数 预测 误差分析 运用bp神经网络进行实验(Fitting function prediction error analysis, using BP neural network for the experiment)
neuralNetwork
- 使用python实现神经网络，以及示例文件(Python implementation of neural networks, as well as examples)
新建文件夹
- 这是BP神经网络的matlab实现，和特征向量的提取(This is the matlab implementation of the BP neural network and the extraction of feature vectors)
GA-BP
- 遗传算法优化BP神经网络，克服原始BP神经网络的缺点，提高算法的精度。(Genetic algorithm, optimization, BP neural networ)
ACATSP
- 旅行商问题(Traveling Saleman Problem，TSP)是车辆路径调度问题(VRP)的特例，由于数学家已证明TSP问题是NP难题，因此，VRP也属于NP难题。旅行商问题（TSP）又译为旅行推销员问题、货郎担问题，简称为TSP问题，是最基本的路线问题，该问题是在寻求单一旅行者由起点出发，通过所有给定的需求点之后，最后再回到原点的最小路径成本(Traveling salesman Problem ('ll Saleman Problem, TSP) is a special case
BP
- 利用BP网络逼近对象y(k)=u(k)^3+y(k-1)/(1+y(k-1)^2)。采样时间取1ms。输入信号为u(k)=0.5sin(6*pi*t)。(Approximate object y (k), =u (k), ^3+y (k-1) / (1+y (k-1) ^2) using BP networks. Sampling time is 1ms. The input signal is u (k) =0.5sin (6*pi*t).)
wine_SVM
- 支持向量机是一种继神经网络之后又一优化的算法推动了机器学习的理论发展。(Support vector machines (SVM) is a kind of optimization algorithm after neural network, which promotes the development of machine learning theory)
wawwa
- Encryption algorithms implemented in c++