LSSVM_psolssvm_pso-LSSVM_回归_lssvm

%LS-SVMh回归测试程序代码模板 %清空变量空间 clc;clear;close all format compact %程序代码计时开始 tic; %数据导入 load('FJ14SumN.mat') %数据预处理 trainset=FJ14SumN(1:1600,1); trainset_label=FJ14SumN(1:1600,2); testset=FJ14SumN(1600:2000,1); testset_label=FJ14SumN(1600:2000,2); %LS-SVM模型参数初始化 type = 'function estimation'; kernel = 'RBF_kernel'; preprocess='original'; gam = 100; sig2 =0.1; %交叉验证优化参数 model=initlssvm(trainset,trainset_label,type,gam,sig2,kernel,preprocess); costfun = 'crossvalidatelssvm'; costfun_args = {10,'mse'}; optfun = 'gridsearch'; model=tunelssvm(model,optfun,costfun,costfun_args) %进行模型训练 model = trainlssvm(model); %回归预测 predictlabel = simlssvm(model,testset); testMAE = mae(abs(predictlabel-testset_label)) testmse=sum((predictlabel-testset_label).^2)/length(testset_label); testrmse=sqrt(testmse) % 结果作图 figure(1) plot(predictlabel,'-kx','LineWidth',1,... 'MarkerEdgeColor','k',... 'MarkerFaceColor','k',... 'MarkerSize',7) hold on plot(testset_label,'-.ko','LineWidth',1,... 'MarkerEdgeColor','k',... 'MarkerFaceColor','w',... 'MarkerSize',7) legend('预测功率','实际功率') title('lssvm预测输出','fontsize',12) ylabel('功率/kW','fontsize',12) xlabel('时间/5min','fontsize',12) % plot(1:length(testset_label),testset_label,'r-',1:length(predictlabel),predictlabel,'b--') % title('秋季（红色为真实值，蓝色为预测值）') % ylabel('功率/kW','fontsize',12) % xlabel('时间/10min','fontsize',12) %程序运行计时结束 toc;