【LSTM分类】基于麻雀算法优化LSTM实现数据分类含Matlab源码

1 简介

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2 部分代码

%_________________________________________________________________________________%  Salp Swarm Algorithm (SSA) source codes version 1.0​%%   Main paper:%   S. Mirjalili, A.H. Gandomi, S.Z. Mirjalili, S. Saremi, H. Faris, S.M. Mirjalili,%   Salp Swarm Algorithm: A bio-inspired optimizer for engineering design problems%   Advances in Engineering Software%   DOI: http://dx.doi.org/10.1016/j.advengsoft.2017.07.002%____________________________________________________________________________________​function [FoodFitness,FoodPosition,Convergence_curve]=SSA(N,Max_iter,lb,ub,dim,fobj)if size(ub,1)==1    ub=ones(dim,1)*ub;    lb=ones(dim,1)*lb;endConvergence_curve = zeros(1,Max_iter);%Initialize the positions of salpsSalpPositions=initialization(N,dim,ub,lb);FoodPosition=zeros(1,dim);FoodFitness=inf;%calculate the fitness of initial salpsfor i=1:size(SalpPositions,1)    SalpFitness(1,i)=fobj(SalpPositions(i,:));end[sorted_salps_fitness,sorted_indexes]=sort(SalpFitness);for newindex=1:N    Sorted_salps(newindex,:)=SalpPositions(sorted_indexes(newindex),:);endFoodPosition=Sorted_salps(1,:);FoodFitness=sorted_salps_fitness(1);%Main loopl=2; % start from the second iteration since the first iteration was dedicated to calculating the fitness of salpswhile l<Max_iter+1    c1 = 2*exp(-(4*l/Max_iter)^2); % Eq. (3.2) in the paper    for i=1:size(SalpPositions,1)        SalpPositions= SalpPositions';        if i<=N/2            for j=1:1:dim                c2=rand();                c3=rand();                %%%%%%%%%%%%% % Eq. (3.1) in the paper %%%%%%%%%%%%%%                if c3<0.5                     SalpPositions(j,i)=FoodPosition(j)+c1*((ub(j)-lb(j))*c2+lb(j));                else                    SalpPositions(j,i)=FoodPosition(j)-c1*((ub(j)-lb(j))*c2+lb(j));                end                %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%            end        elseif i>N/2 && i<N+1            point1=SalpPositions(:,i-1);            point2=SalpPositions(:,i);            SalpPositions(:,i)=(point2+point1)/2; % % Eq. (3.4) in the paper        end        SalpPositions= SalpPositions';    end    for i=1:size(SalpPositions,1)        Tp=SalpPositions(i,:)>ub';Tm=SalpPositions(i,:)<lb';SalpPositions(i,:)=(SalpPositions(i,:).*(~(Tp+Tm)))+ub'.*Tp+lb'.*Tm;        SalpFitness(1,i)=fobj(SalpPositions(i,:));        if SalpFitness(1,i)<FoodFitness            FoodPosition=SalpPositions(i,:);            FoodFitness=SalpFitness(1,i);         end    end    Convergence_curve(l)=FoodFitness;    l = l + 1;end​

3 仿真结果

4 参考文献

[1]陶晓玲, 王素芳, 赵峰,等. 基于麻雀搜索算法优化Bi-LSTM的网络安全态势预测方法:. ​

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