回归预测 | Matlab基于SMA+WOA+SFO-LSSVM多输入单输出回归预测
目录
- 回归预测 | Matlab基于SMA+WOA+SFO-LSSVM多输入单输出回归预测
- 效果一览
- 基本介绍
- 程序设计
- 参考资料
效果一览
基本介绍
SMA+WOA+SFO-LSSVM回归预测
基于黏菌算法+鲸鱼算法+向日葵算法优化LSSVM回归预测
其中包含三种改进模型和原始模型对比
SMA-LSSVM,
WOA-LSSVM,
SFO-LSSVM,
LSSVM
四种模型对比
评价指标:R2,MSE,RMSE,MAPE训练集测试集都有,预测结果图见下图
Matlab程序!
程序设计
- 完整源码和数据获取方式私信回复Matlab基于SMA+WOA+SFO-LSSVM多输入单输出回归预测。
function
while t<=Tmax
r2=rand;
for i=1:Pop_size
U1=rand(1,dim)>rand;
if rand<rand %% Exploration phase
if rand<rand %% First defense mechanism
%% Calculate y_t
y=(X(i,:)+X(randi(Pop_size),:))/2;
X(i,:)=X(i,:)+(randn).*abs(2*rand*Gb_Sol-y);
else %% Second defense mechanism
y=(X(i,:)+X(randi(Pop_size),:))/2;
X(i,:)=(U1).*X(i,:)+(1-U1).*(y+rand*(X(randi(Pop_size),:)-X(randi(Pop_size),:)));
end
else
Yt=2*rand*(1-t/(Tmax))^(t/(Tmax));
U2=rand(1,dim)<0.5*2-1;
参考资料
[1] https://blog.csdn.net/kjm13182345320/article/details/129215161
[2] https://blog.csdn.net/kjm13182345320/article/details/128105718