MAT之ELM：ELM基于近红外光谱的汽油测试集辛烷值含量预测结果对比

MAT之ELM：ELM基于近红外光谱的汽油测试集辛烷值含量预测结果对比

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输出结果

代码设计

%ELM：ELM基于近红外光谱的汽油测试集辛烷值含量预测结果对比—Jason niu
load spectra_data.mat 

temp = randperm(size(NIR,1));

P_train = NIR(temp(1:50),:)';
T_train = octane(temp(1:50),:)';

P_test = NIR(temp(51:end),:)';
T_test = octane(temp(51:end),:)';
N = size(P_test,2);

[Pn_train,inputps] = mapminmax(P_train);
Pn_test = mapminmax('apply',P_test,inputps);

[Tn_train,outputps] = mapminmax(T_train);
Tn_test = mapminmax('apply',T_test,outputps);

[IW,B,LW,TF,TYPE] = elmtrain(Pn_train,Tn_train,30,'sig',0);

tn_sim = elmpredict(Pn_test,IW,B,LW,TF,TYPE);

T_sim = mapminmax('reverse',tn_sim,outputps);

result = [T_test' T_sim'];

E = mse(T_sim - T_test);

N = length(T_test);
R2=(N*sum(T_sim.*T_test)-sum(T_sim)*sum(T_test))^2/((N*sum((T_sim).^2)-(sum(T_sim))^2)*(N*sum((T_test).^2)-(sum(T_test))^2)); 

figure(1)
plot(1:N,T_test,'r-*',1:N,T_sim,'b:o')
grid on
legend('真实值','预测值')
xlabel('样本编号')
ylabel('辛烷值')
string = {'ELM：ELM基于近红外光谱的汽油测试集辛烷值含量预测结果对比—Jason niu';['(mse = ' num2str(E) ' R^2 = ' num2str(R2) ')']};
title(string)

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ELM：ELM基于近红外光谱的汽油测试集辛烷值含量预测结果对比