资源列表
BP
- BP神经网络实现多分类，代码包括六分类以及二分类(The BP neural network implements multiple classifications. The code includes six categories and two categories.)
Force_calculate
- 等效法计算气隙磁通及涡流阻尼器阻尼力，边界条件算法(The equivalent method is used to calculate the air gap flux and the damping force of the eddy current damper. The boundary condition algorithm)
nihe
- [1] 对 sin2pix进行在x=0进行泰勒展开 [2] 曲线拟合 python(curve fitting Taylor expansion sin(2pix))
idocdown_33lc.com
- 帮助学习分水岭变换是一种常用有效的图像分割方法。针对分水岭的过分割问题,对分水岭分割后的图像,(Study aid A ccordin g tO the analysis of eigenvalue and relativity it w as fcIund that ban ds of T M 3 T M 4 and T M 5 had sm all relativity and contain am ple inform ation)
Desktop
- 在线电子商城系统，共分为注册登录模块，商品管理模块，账户管理模块，订单管理模块等。(The online electronic business city system is divided into registered login module, commodity management module, account management module, order management module and so on.)
Couette
- 库艾特流的样本代码（包含显式解和隐式解）(Couette flow sample code with both explicit and implicit method.)
prestress2dto3d
- 二维坐标转化为三维坐标，常用于预应力钢筋位置确定(Two dimensional coordinates are transformed into three dimensional coordinates, which are commonly used to determine the position of prestressed reinforcement)
NSGA2算法源代码
- nsga2,多目标遗传算法，从别处搜索而来，非matlab(nsga2 no matlab, just for c, that's all)
GeneticAlgorithm
- 使用传统的遗传算法解决0-1背包问题，其中使用的是轮盘选择、最简单的随机交叉变异(Using traditional genetic algorithm to solve the 0-1 knapsack problem)
Sort
- 主流O(n^2)和O(n*logn)的排序算法的实现和部分算法的优化。以及算法的性能测试。可以很直观的展现算法性能和实现过程。(The implementation of the sorting algorithm for the mainstream O (n^2) and the O (n*logn) and the optimization of some algorithms. And the performance test of the algorithm. It can show
Three-methods-for-VRP
- 包括遗传算法，构建法和改进法在内的3种方法实现VRP问题。供初学者学习和参考(3 methods, including genetic algorithm, construction method and improved method, are used to realize the VRP problem. For beginners to learn and refer to)
MATLAB-floyd
- Floyd算法又称为弗洛伊德算法，插点法，是一种用于寻找给定的加权图中顶点间最短路径的算法。(The Floyd algorithm, also called the Freud algorithm and the insertion point method, is an algorithm for finding the shortest path between the vertices in a given weighted graph.)