ABAQUS技巧积累

说明：  中国电子科技集团公司认知与智能技术重点实验室发布的MaCA（Multi-agent Combat Arena）环境，是国内首个可模拟军事作战的轻量级多智能体对抗与训练平台，是多智能体对抗算法研究、训练、测试和评估的绝佳环境，可支持作战场景和规模自定义，智能体数量和种类自定义，智能体特征和属性自定义，支持智能体行为回报规则和回报值自定义等。(MaCA (multi agent combat) issued by the Key Laboratory of cognitive and intelligent technology of China Electronic Technology Corporation Arena) environment is the first lightweight multi-agent confrontation and training platform that can simulate military operations in China. It is an excellent environment for the research, training, testing and evaluation of multi-agent confrontation algorithms. It can support the customization of battle scenarios and scales, the number and types of agents, the characteristics and attributes of agents, and the behavior return rules and values of agents And so on.)

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)

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)

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.)

说明：  GRNN网络的预测——基于广义回归神经网络的货运量预测(Prediction of GRNN Network-- Freight Volume Forecast based on Generalized regression Neural Network)

说明：  tarjan算法求解有向图中的简单环，非常好用(Tarjan algorithm is very useful for solving simple rings in directed graphs.)

说明：  关于极限学习机的回归拟合，还有分类的实例程序(On the regression fitting of the limit learning machine and the example program of classification)

说明：  魔术轮胎公式，车辆动力学中常用的关于轮胎的建模(magic tire,used in vehicle model.)

matlab实现人体回波模型创建和短时傅里叶测试(Matlab realization of human echo model and short time Fourier test)

说明：  对于非线性模型的跟踪预估问题，摒弃额对非线性函数进行线性化的做法，采用无迹变换处理均值和方差的非线性传递问题。(For the tracking and prediction problem of the nonlinear model, the linearization of the non-linear function is abandoned, and the traceless transformation is used to deal with the non-linear transfer of mean and variance.)