蚁群算法uav解最优路径

这个程序是雷达信号处理中的恒虚警检测算法，使用matalab语言编写，运行即可使用。(This program is constant false alarm detection in radar signal processing algorithm, using matalab language, running can be used.)

实现了random waypoint模型(random waypoint model)

说明：  在fluent仿真软件中定义DPM两相流计算(Fluent user defined DPM Model)

说明：  对事件触发控制进行仿真，并使其最终结果达到稳定(The event trigger control is simulated and the final result is stable)

可用于车辆操控稳定性分析，预测车辆行驶状态进行预测控制。(Can be used for vehicle control stability analysis, forecast vehicle driving state for predictive control.)

估算锂电池soc的MATLAB simulink模型(MATLAB Simulink model for estimating SOC of lithium battery)

稳健波束形成中的mvdr（最小方差无畸变失真响应）算法(robust adaptive bearforming mvdr)

通过matlab编程实现了比例导引法制导的弹目飞行的轨迹生成(Trajectory Generation of Missile Guided by Proportional Guidance Method)

这个是信号与处理专业的大作业，主要研究两个方面的问题：低通滤波器的阶跃响应特性分析和连续线性系统的求解。通过这次课程设计，将会研究Matlab的一些基本的数值计算应用方法，对计算结果进行形象化地展示，有利于加深对本课程内容的理解。(This is a major task of signal and processing specialty. It mainly studies two aspects: step response characteristic analysis of low-pass filter and solution of continuous linear system. Through this course design, we will study some basic numerical calculation application methods of MATLAB, and visualize the calculation results, which is conducive to deepening the understanding of the course content.)

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.)