【DVHop定位】基于金枪鱼优化算法TSO优化无线传感器非测距定位DVHop附Matlab代码

✅作者简介热爱科研的Matlab仿真开发者擅长毕业设计辅导、数学建模、数据处理、算法改进、程序设计科研仿真。完整代码获取 定制创新 论文复现私信个人信条做科研博学之、审问之、慎思之、明辨之、笃行之是为博学慎思明辨笃行。 内容介绍一、引言无线传感器网络WSN在环境监测、智能家居、工业控制等众多领域有着广泛应用。在这些应用中准确获取传感器节点的位置信息至关重要。DVHop 作为一种经典的非测距定位算法以其低功耗、低成本的特点被广泛采用。然而DVHop 算法存在一些局限性例如定位误差较大。金枪鱼优化算法TSO是一种新兴的智能优化算法模拟金枪鱼的捕食、集群和探索行为具有良好的全局搜索能力。将 TSO 应用于优化 DVHop 算法有望提高无线传感器的定位精度。二、DVHop 算法原理跳数获取在 WSN 中锚节点已知位置的节点向其邻居节点广播包含自身位置和跳数初始为 0的消息。邻居节点接收到消息后将跳数加 1并继续向其邻居节点转发直到网络中的所有节点都接收到至少一个锚节点的消息。通过这种方式每个节点都能记录下到各个锚节点的跳数。⛳️ 运行结果 部分代码%___________________________________________________________________%% Tuna swarm optimization (TSO) %% %% Developed in MATLAB R2016b %% %% Author and programmer: Andi Tang %% %% E-mail: 418932433qq.com %% andisu_afeu163.com %% %% Main paper: Tuna swarm optimization: A novel swarm-based %% metaheuristic algorithm for global optimization %% DOI: 10.1155/2021/9210050 %% Computational Intelligence and Neuroscience%% %% %%___________________________________________________________________%function [Tuna1_fit,Tuna1,Convergence_curve]TSO(Particles_no,Max_iter,Low,Up,Dim,fobj)Tuna1zeros(1,Dim); Tuna1_fitinf;Tinitialization(Particles_no,Dim,Up,Low);Iter0;aa0.7;z0.05;while IterMax_iterCIter/Max_iter;a1aa(1-aa)*C;a2(1-aa)-(1-aa)*C;for i1:size(T,1)Flag4ubT(i,:)Up;Flag4lbT(i,:)Low;T(i,:)(T(i,:).*(~(Flag4ubFlag4lb)))Up.*Flag4ubLow.*Flag4lb;fitness(i)fobj(T(i,:));if fitness(i)Tuna1_fitTuna1_fitfitness(i); Tuna1T(i,:);endend%---------------- Memory saving-------------------if Iter0fit_oldfitness; C_oldT;endfor i1:Particles_noif fit_old(i)fitness(i)fitness(i)fit_old(i); T(i,:)C_old(i,:);endendC_oldT; fit_oldfitness;%-------------------------------------------------t(1-Iter/Max_iter)^(Iter/Max_iter);if randzT(1,:) (Up-Low)*randLow;elseif 0.5randr1rand;Betaexp(r1*exp(3*cos(pi*((Max_iter-Iter1)/Max_iter))))*(cos(2*pi*r1));if CrandT(1,:)a1.*(Tuna1Beta*abs(Tuna1-T(1,:)))a2.*T(1,:); %Equation (8.3)elseIndivRandrand(1,Dim).*(Up-Low)Low;T(1,:)a1.*(IndivRandBeta*abs(IndivRand-T(i,:)))a2.*T(1,:);%Equation (8.1)endelseTF (rand0.5)*2-1;if 0.5randT(1,:)Tuna1rand(1,Dim).*(Tuna1-T(1,:))TF.*t^2.*(Tuna1-T(1,:));%Equation (9.1)elseT(1,:) TF.* t^2.*T(1,:);%Equation (9.2)endendendfor i2:Particles_noif randzT(i,:) (Up-Low)*randLow;elseif 0.5randr1rand;Betaexp(r1*exp(3*cos(pi*((Max_iter-Iter1)/Max_iter))))*(cos(2*pi*r1));if CrandT(i,:)a1.*(Tuna1Beta*abs(Tuna1-T(i,:)))a2.*T(i-1,:);%Equation (8.4)elseIndivRandrand(1,Dim).*(Up-Low)Low;T(i,:)a1.*(IndivRandBeta*abs(IndivRand-T(i,:)))a2.*T(i-1,:);%Equation (8.2)endelseTF (rand0.5)*2-1;if 0.5randT(i,:)Tuna1rand(1,Dim).*(Tuna1-T(i,:))TF*t^2.*(Tuna1-T(i,:)); %Equation (9.1)elseT(i,:) TF*t^2.*T(i,:);%Equation (9.2)endendendendIterIter1;Convergence_curve(Iter)Tuna1_fit;end 参考文献更多免费数学建模和仿真教程关注领取