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自信车轮压力分析 python 源代码 有限元分析(Wheel of bike ，python Finite Element code)

层次分析法确定权重必备，是一款实用的小软件(AHP to determine the weights necessary, is a small software utility)

滤波求和方式实现宽带波束形成，从先验概率中采样，计算权重，最小均方误差（MMSE）的算法。( Filtering summation way broadband beamforming, Sampling a priori probability, calculate the weight, Minimum mean square error (MMSE) algorithm.)

：针对三容水箱是较为典型的非线性、时延对象，具有很强的代表性这一特点， 通过机理建模方法建立了三容水箱的一般数学模型。分析了线性和非线性阻力板的流量特性， 并通过实验测定了阻力板流量系数。最后给出了三容水箱的线性化模型。由仿真实验可知，非线性模型的阶跃响应和实验测得的响应曲线相吻合，(: For three-tank water tank is a more typical non-linear, time-delay object, has a strong representation of this characteristic, through the mechanism of modeling methods allow the establishment of three general mathematical model of water tanks. Analysis of linear and nonlinear flow resistance characteristics of plate, and through experimental determination of the resistance plate flow coefficient. Finally, the three-linear model of water tanks. By simulation experiments, we can see that the nonlinear model of step response and the experimentally measured response curve coincide)

最小二乘拟合空间直线，和单独的误差计算函数(Linear least squares fitting space, and a separate error calculation function)

三维的有限时域差分源程序，边界条件为pml(Three-dimensional FDTD source, boundary conditions for the PML)

利用表达式求解和栈的只是，设计一个简易的数学题库， 可供小学生作业，并能给出分数。 要求：建立试题库文件，随机产生 n 个题目；题目涉及加减乘除，带括弧的混合运算；随时可以退出；保留历史分数，能回顾历史，给出与历史分数比较后的评价。(Use solving expressions and stack just design a simple math exam, students for the job, and can give a score. Requirements: Create test file, randomly generating n topics topics involving addition, subtraction with parentheses mixing operation ready to quit keep historical scores, can look back at history, and history is given uation scores after comparison.)

详细全面的蒙特卡洛PPT讲解以及MATLAB算例，帮助大家0基础快速掌握MC的精华所在。(Detailed and comprehensive Monte Carlo PPT to explain and MATLAB example, to help you basically grasp the essence of MC.)

matlab程序—用burg方法计算太阳黑子爆发的周期(the matlab program-the frequency of the sunspot by the method of burg)

用Python语言写的多目标进化算法库（2017年最新版本），包含常见的多目标进化算法以及当前最新文献中的最新算法，能够实现不同算法之间的性能比较（包含常见的GD, IGD, HV等评价指标自动生成）。可以供进化计算、多目标优化、单目标优化算法的学习参考。Python语言版本简单易懂，实用性强。(Library of multi-objective evolutionary algorithm written in Python language (the latest version in 2017), including multi-objective evolutionary algorithm and the most common new literature in the new algorithm, can realize the performance between different methods (including the common GD, IGD, HV and other evaluation index generation). It can be used as a reference for evolutionary computation, multi-objective optimization and single objective optimization. Python language version is simple and easy to understand, practical.)