rand_int

matlab 最优化算法 matlab 最优化算法matlab 最优化算法 matlab 最优化算法(matlab zui you hua suan f a)

这是编好的程序[cp,zq]=grnn(data,yy) gaussian SVM，GRNN 的正确率，击中率，正确拒绝率在19个先天盲人中的为： SVM GRNN 0.68421 0.73684 0.83333 0.83333 0.42857 0.57143 解压到MATLAB的TOOLBOX文件夹里，然后刷新工具箱，在命令窗口输入：rehash toolboxcache。 然后就可以用我的那个函数了。( It is programmed procedures [cp, zq] = grnn (data, yy) gaussian SVM, GRNN accuracy rate, hit rate and correct rejection rate in the 19 congenital blind as follows: SVM GRNN 0.68421 0.73684 0.83333 0.83333 0.42857 0.57143)

分析了支持向量回归机在能源需求预测中的优势,确定了输入向量集合和输出向量集合,建立了基于Matlab技术的SVR能源需求预测模型.对我国1985-2008年能源需求相关数据进行模拟与仿真,并对中国2010年和2020年能源需求量进行预测.研究结果表明:一是中国未来对能源的需求量逐渐增加,从2010年的330400万吨标准煤上升到2020年418320万吨标准煤,年均增长率为2.39％；二是在解决我国能源系统小样本.非线性及高维模式识别问题中SVR比BP神经网络等方法有更高的预测精度.(Support vector regression analyzes advantage in energy demand forecast to determine the set of input vectors and output vector set, established SVR energy demand forecasting model based on Matlab technology. Energy demand for our 1985-2008 related data modeling and simulation , and China in 2010 and 2020 energy demand forecast results show that: First, China s increasing demand for energy in the future, from 3.304 billion tons of standard coal in 2010 rose to 4.1832 billion tons of standard coal in 2020, average annual growth rate of 2.39 second is to solve our energy system small sample nonlinear and high dimensional pattern recognition problem SVR higher prediction accuracy than the BP neural network method.)

matlab中电气化铁路上每1km长的牵引网的等效阻抗模型。(matlab in every 1km long electrified railway traction network equivalent impedance model.)

Etude et Simulation d’estimateurs et observateurs robustes de flux et de vitesse pour la machine asynchrone

Prediction. A system which produces the prediction error.

MATLAB和VC接口编程的详细介绍，介绍了简单常见的方法。(MATLAB and VC programming interfaces in detail introduce a simple common approach.)

MATLAB6_0基础及应用 _ 清源计算机工作室编著_ - [出版地不详]_ 机构_0(the basic knowledge of matlab6.0)

Advanced Numerical Methods FTCS implicit

说明：  事件触发控制的仿真，遗传算法简介，多智能体协同等问题(The simulation of event triggered control, the introduction of genetic algorithm and the related discussion of multi-agent cooperation.)