▍1. Kalman滤波处理运动小球圆心位置
说明: 用卡尔曼滤波方法预测目标轨迹,能够估计目标下一时刻的位置信息(Prediction of Target Trajectory by Kalman Filter)
说明: 用卡尔曼滤波方法预测目标轨迹,能够估计目标下一时刻的位置信息(Prediction of Target Trajectory by Kalman Filter)
基于杂草算法Kohonen网络入侵检测 (Weeds algorithm based on Kohonen network intrusion detection)
有关微动的程序,包括转动,锥动,有需要的可以下载(Fretting about the program, including rotation, moving cone, there is a need to download)
说明: 波浪模拟,线性波、随机波、船舶受波浪力模拟。(Wave simulation includes linear wave, random wave and wave force on ship.)
matlab程序,标准IEEE33节点系统潮流计算程序。(Matlab program, standard IEEE33 node system power flow calculation program.)
说明: 将训练之后的模型进行测试,对单幅图像进行相应的去雨(Removing rain from single images via a deep detail network)
基于NSGA2的柔性作业车间调度问题(FJSP-NSGA2)(Flexible job shop scheduling problem based on NSGA2 Matlab Code(FJSP-NSGA2))
计算超体积测度,方便简单实用,尽请下载...(hypervolume calculator)
说明: GA-BPNN实例,包含样本数据和函数代码,测试可运行。(example of GA-BPNN, data and matlab codes are included.)
基于buck型变换器的滑模变结构控制仿真(Simulation of sliding mode variable structure control based on Buck Converter)
说明: 基于buck型变换器的滑模变结构控制仿真(Simulation of sliding mode variable structure control based on Buck Converter)
说明: T-MATS 是一个开源的热力学模型包。它提供了一个 MATLAB/Simulink 工具箱,可以让开发者模拟涡轮机和燃气涡轮机来建立热力学系统。(T-mats is an open source thermodynamic model package. It provides a Matlab / Simulink toolbox that allows developers to simulate turbines and gas turbines to build thermodynamic systems.)
说明: 利用粒子群算法进行优化调度,以经济性为目标函数,完全可以运行(The particle swarm optimization algorithm is used to optimize the scheduling, which takes the economy as the objective function and can run completely)
逾渗网络模型的绘制,可以任意设置孔隙和网络的参数以及流体类型。(Percolation_network drawing)
说明: Matlab可以使用fitrsvm创建回归支持向量机模型。fitrsvm在中低维预测变量数据集上训练或交叉验证支持向量机(SVM)回归模型。 fitrsvm支持使用内核函数映射预测变量数据,并支持通过二次编程实现目标函数最小化。要在高维数据集(即包含许多预测变量的数据集)上训练线性SVM回归模型,请改用fitrlinear。(Matlab can use fitrsvm to create regression support vector machine model. Fitrsvm trains or cross validates the support vector machine (SVM) regression model on the medium and low dimensional prediction variable data set. Fitrsvm supports the use of kernel function mapping to predict variable data, and supports the goal function minimization through secondary programming. To train a linear SVM regression model on a high-dimensional dataset (that is, a dataset containing many predictors), use fitrlinear instead.)
This codes belongs to the paper: Decentralized Hypothesis Testing in Energy Harvesting Wireless Sensor Networks
说明: This codes belongs to the paper: Decentralized Hypothesis Testing in Energy Harvesting Wireless Sensor Networks
说明: 基于遗传算法与最小二乘支持向量机的特征选择的烟叶识别(GA-LSSVMlabv1_8_R2016b_)