wurenji

包括GPS仿真的全套代码，matlab和C#。GPS信号的模拟、捕获、追踪，以及数据的处理，极限的解算，周跳的探测及整周模糊度的接算。有用的资料与大家共享后才能体现其价值，希望同仁们也能及时共享比较好的资料，大家一同探讨、进步。(ncludes a full set of GPS simulation code, matlab and C#. GPS signal simulation, capture, tracking, and data processing, limit solution, cycle slip detection and integer ambiguity. Only when useful information is shared with all of you can it reflect its value. We hope that colleagues can also share better information in time, and everyone will discuss and progress together.)

机械动力学进行模态分析，频响应分析等动力学的分析(Modal analysis, frequency response analysis and other dynamic analysis of mechanical dynamics.)

说明：  利用遗传算法求解TSP问题，具有比较实际的应用价值(It has practical application value to solve TSP problem by genetic algorithm)

Incoherent Scatter Radar model in Matlab. To calculate the theoretical spectra of radars.

说明：  运用卡尔曼滤波器，在已有条件下，用matlab软件得到与已知的飞行器轨迹相同的预测轨迹(Kalman filter is used to predict the flight path of the aircraft)

说明：  周期边界，通过python代码实现，abaqus多尺度仿真，有效性能计算，复合材料(Periodic boundary, implemented by Python code, ABAQUS multi-scale simulation, effective performance calculation, composite materials)

说明：  对目标追踪的ekf算法，pf算法，ukf算法的比较，误差分析(Comparison and error analysis of EKF algorithm, PF algorithm and UKF Algorithm for target tracking)

说明：  龙门吊反演滑膜变结构控制，simlink程序+s函数程序，亲测有效(Sliding membrane control of gantry crane inversion)

基于CARSIM的驾驶员预瞄模型实现无人车路径跟踪(The pilot model realizes the path tracking of the driverless car)

大坝变形的精确预测对其安全评价方面发挥着重要作用。为了进一步提高大坝变形预测精度，提出了一种改进的灰狼算法优化支持向量机的预测模型。通过引入非线性收敛因子和采用动态加权策略，提升灰狼算法优化支持向量机惩罚因子和核函数参数的能力，并以优化的参数来建立支持向量机大坝变形预测模型。选取实例数据，在与布谷鸟算法、差分进化算法、粒子群算法、基本灰狼算法优化的支持向量机预测比较中，实验结果表明，改进的灰狼算法对支持向量机参数的优化是有效的，可以提高大坝变形预测精度。(Accurate prediction of dam deformation plays an important role in its safety evaluation. In order to further improve the prediction accuracy of dam deformation, an improved grey Wolf algorithm is proposed to optimize the prediction model of support vector machine. By introducing the nonlinear convergence factor and using the dynamic weighting strategy, the gray wolf algorithm is improved to optimize the capacity of the support vector machine penalty factor and the kernel parameter, and the support vector machine dam deformation prediction model is established with the optimized parameters. The experimental results show that the Improved Grey Wolf algorithm is effective for the optimization of support vector machine parameters, and it can improve the accuracy of the deformation prediction of the dam.)