nenkiu_v58

基于配电网络辐射型的前推回代潮流计算程序，包括分层等内容(And backward substitution based on the radiation type of distribution network before flow calculation procedures, including the contents of the stratification)

ABAQUS的二次开发，非常适合学习VDLOAD的同志们学习，来自廖公云老师的《ABAQUS有限元软件在道路工程中的应用》(Learning from Liao Gongyun teacher "ABAQUS finite element software ABAQUS secondary development, very for learning VDLOAD, comrades in road works")

采用数值分析课程中的插值逼近以及曲面拟合方法来估算复杂的函数表达式。(Interpolation approximations and surface fitting methods are used in the numerical analysis course to estimate complex function expressions.)

说明：  模糊模拟、神经网络以及遗传算法的结合，matlab程序(The combination of fuzzy simulation, neural network and genetic algorithm, matlab program)

SPH方法计算二维溃坝问题的源程序，个人觉得还可以(Two-dimensional dam break problem SPH method the source, individuals felt that I could)

最小二乘法的证明及matlab程序，附有文字说明和程序源码(The method of least squares)

三次样条曲线拟合代码，先训练，后差值，计算非常准确(Three times spline curve fitting, the first training, and after, computation is very accurate)

基于递推最小二乘法进行系统辨识的基本原理,对给定的实际输入输出数据运用MATLAB的M语言编写递推最小二乘算法(The basic principle of system identification based on recursive least squares method, using the MATLAB M language to write recursive least squares algorithm for given actual input and output data)

粒子群算法，也称粒子群优化算法或鸟群觅食算法（Particle Swarm Optimization），缩写为 PSO。它具有精度高，收敛快等优点，广泛用于系统辨识、函数优化等领域。文件pso.m是粒子群算法辨识程序，在此基础上，需要自行编写目标函数计算程序以实现不同系统的参数辨识。(Particle swarm optimization (PSO), also known as particle swarm optimization algorithm or bird swarm foraging algorithm (Particle Swarm Optimization), abbreviated as PSO. It has the advantages of high precision and fast convergence. It is widely used in system identification, function optimization and other fields. The document pso.m is a particle swarm algorithm identification program. On this basis, it is necessary to write an object function calculation program to realize the parameter identification of different systems.)

matlab环境下，克里金插值中用回归方法和线性方法拟合出的球状模型的系数。(Kriging the spherical model coefficients using regression fitting in matlab.)