Simulink资料128mdl

说明：  flac3d自便模型，二次开发邓肯张模型，(The two time development of Duncan's Duncan Zhang model)

说明：  三分之一倍频程程序，信号处理必备，请自用下载(One-third octave program, self-download)

参加中国科学软件网组织的PSCAD研讨会ppt，里有过电压模型、次同步振荡SSR、风力发电模型(China Software Network participated in scientific seminars organized PSCAD ppt, there are over-voltage model, SSO SSR, wind power generation model)

说明：  数值方法求解常微分方程的实验例题，由matlab语言实现(Numerical method to solve experimental examples of ordinary differential equations, realized by matlab language)

这是一个Python基础的练习Demo,提供以后进行学习查看和记忆(this is a Python basic traning Demo,Provide for future learning, viewing and memory)

说明：  设计一八木天线，振子数目为4，长度分别为：反射器长度0.39，主馈振子长度0.356，引向器长度均为0.3；反射器和主馈振子的距离0.265，主馈振子和第一引向器的距离0.2575，第一引向器和第二引向器的距离0.225。天线工作频率为400MHz，各振子分段数为9。 利用矩量法模拟该天线的电流分布，并绘制方向图。(A eight wood antenna is designed. The number of vibrators is 4 and the length is 0.39 for the reflector, 0.356 for the main feeder and 0.3 for the director. The distance between the reflector and the main feeder is 0.265, 0.2575 for the main feeder and the first director. The distance between the first director and the second director is 0.225. The working frequency of the antenna is 400MHz and the number of segments of each vibrator is 9.)

c语言编程100例，介绍了一些问题的编程-Language programming of 100 cases

ct reconstruction matlab code

说明：  演示基于蚁群算法的三维路径规划算法。蚁群算法是由Marco Dorigo博士，在1992年他的博士论文中提出的，其主要灵感来源于蚂蚁在寻找食物过程中发现路径的行为。蚁群算法是一种模拟进化算法，研究表明该算法具有许多优良的性质。通过对PID控制器参数优化设计方面的问题，将蚁群算法设计的结果与遗传算法设计的结果进行了比对，数值仿真结果表明，蚁群算法是一种新的模拟进化的优化方法，显示出了其适用于组合优化类问题求解的优越特性。(Demonstrate the three-dimensional path planning algorithm based on ant colony algorithm. The ant colony algorithm is proposed by Dr. Marco Dorigo in his doctoral thesis in 1992. Its main inspiration is the behavior of ants finding the path in the process of finding food. Ant colony algorithm is a kind of simulated evolutionary algorithm, which has many excellent properties. By comparing the results of ant colony algorithm with the results of genetic algorithm, the results of numerical simulation show that ant colony algorithm is a new evolutionary optimization method, which shows its superiority in solving combinatorial optimization problems.)

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