创新发文基于凌日优化算法TSOA-DELM的多输入单输出预测Matlab实现.rar

function [Best_Planet , best,Bestss] = TransitSearch (ns,maxcycle,Vmin,Vmax,nvar,CostFunction) SN=10; %% Initialization Empty.Location = []; Empty.Cost = inf; Galaxy_Center = repmat (Empty, 1, 1); region = repmat (Empty, ns*SN, 1); selested_regions = repmat (Empty, ns, 1); Stars = repmat (Empty, ns, 1); Stars_sorted = zeros(ns,1); Ranks = 1:1:ns; Stars_Ranks = zeros(ns,1); Luminosity = zeros(ns,1); Star_RanksNormal = zeros(ns,1); Distance = zeros(ns,1); Transit0 = zeros(ns,1); SN_P = repmat (Empty, SN, 1); Bests=region; if length(Vmin) >1 Vmin=Vmin; Vmax=Vmax; else Vmin=Vmin*ones(1,nvar); Vmax=Vmax*ones(1,nvar); end %% Galaxy Phase % Initial Location of The Center of the Galaxy Galaxy_Center.Location = unifrnd(Vmin,Vmax,1,nvar); % Galaxy_Center.Location=initialization(ns,nvar,Vmax,Vmin); Galaxy_Center.Cost = CostFunction(Galaxy_Center.Location); % Galactic Habitate Zone of the Galaxy for l = 1:ns*SN zone = randi(2); if zone ==1 difference = rand().*(Galaxy_Center.Location)-(unifrnd(Vmin,Vmax,1,nvar)); else difference = rand().*(Galaxy_Center.Location)+(unifrnd(Vmin,Vmax,1,nvar)); end Noise = ((rand(1,nvar)).^3).*(unifrnd(Vmin,Vmax,1,nvar)); region(l).Location = Galaxy_Center.Location + difference - Noise; region(l).Location = max(region(l).Location, Vmin); region(l).Location = min(region(l).Location, Vmax); region(l).Cost = CostFunction(region(l).Location); end % Selection of Stars from the Galactic Habitate Zone of the Galaxy [Sort,index]=sort([region.Cost]); for i = 1:ns selested_regions(i) = region(i); for k = 1:SN zone = randi(2); if zone ==1 difference = rand().*(selested_regions(i).Location)-rand().*(unifrnd(Vmin,Vmax,1,nvar)); else difference = rand().*(selested_regions(i).Location)+rand().*(unifrnd(Vmin,Vmax,1,nvar)); end Noise = ((rand(1,nvar)).^3).*(unifrnd(Vmin,Vmax,1,nvar)); new.Location = selested_regions(i).Location + difference - Noise; new.Location = max(new.Location, Vmin); new.Location = min(new.Location, Vmax); new.Cost = CostFunction(new.Location); if new.Cost < Stars(i).Cost Stars(i) = new; end end end % Initial Location of the Best Planets (Start Point: Its Star) Best_Planets = Stars; % Specification of the Best Planet [Sort,index]=sort([Best_Planets(1).Cost]); Best_Planet = Best_Planets(index(1,1)); % Telescope Location Telescope.Location = unifrnd(Vmin,Vmax,1,nvar); % Determination of the Luminosity of the Stars for i = 1:ns Stars_sorted(i,1) = Stars(i).Cost; end Stars_sorted = sort (Stars_sorted); for i = 1:ns for ii = 1:ns if Stars(i).Cost == Stars_sorted(ii,1) Stars_Ranks(i,1) = Ranks(1,ii); Star_RanksNormal(i,1) = (Stars_Ranks(i,1))./ns; end end Distance(i,1) = sum((Stars(i).Location-Telescope.Location).^2).^0.5; Luminosity(i,1) = Star_RanksNormal(i,1)/((Distance(i,1))^2); end Luminosity_new = Luminosity; Stars2 = Stars; %% Loops of the TS Algorithm for it = 1:maxcycle %% Transit Phase Transit = Transit0; Luminosity = Luminosity_new; for i = 1:ns difference = (2*rand()-1).*(Stars(i).Location); Noise = ((rand(1,nvar)).^3).*(unifrnd(Vmin,Vmax,1,nvar)); Stars2(i).Location = Stars(i).Location + difference - Noise; Stars2(i).Location = max(Stars2(i).Location, Vmin); Stars2(i).Location = min(Stars2(i).Location, Vmax); Stars2(i).Cost = CostFunction(Stars2(i).Location); end for i = 1:ns Stars_sorted(i,1) = Stars2(i).Cost; end Stars_sorted = sort (Stars_sorted); for i = 1:ns for ii = 1:ns if Stars2(i).Cost == Stars_sorted(ii,1) Stars_Ranks(i,1) = Ranks(1,ii); Star_RanksNormal(i,1) = (Stars_Ranks(i,1))./ns; end end Distance(i,1) = sum((Stars2(i).Location-Telescope.Location).^2).^0.5; Luminosity_new(i,1) = Star_RanksNormal(i,1)/((Distance(i,1))^2); if Luminosity_new(i,1) < Luminosity(i,1) Transit (i,1) = 1; % Has transit been observed? 0 = No; 1 = Yes end end Stars = Stars2; %% Location Phase (Exploration) for i = 1:ns if Transit (i,1) == 1 % Determination of the Location of the Planet Luminosity_Ratio = Luminosity_new(i,1)/Luminosity(i,1); Planet.Location = (rand().*Telescope.Location + Luminosity_Ratio.*Stars(i).Location)./2; for k = 1:SN zone = randi(3); if zone ==1 new.Location = Planet.Location - (2*rand()-1).*(unifrnd(Vmin,Vmax,1,nvar)); elseif zone ==2 new.Location = Planet.Location + (2*rand()-1).*(unifrnd(Vmin,Vmax,1,nvar)); else new.Location = Planet.Location + (2.*rand(1,nvar)-1).*(unifrnd(Vmin,Vmax,1,nvar)); end new.Location = max(new.Location, Vmin); new.Location = min(new.Location, Vmax); % new.Cost = CostFunction(new.Location); SN_P(k) = new; end SUM = 0; for k = 1:SN SUM = SUM+SN_P(k).Location; end new.Location = SUM./SN; new.Cost = CostFunction(new.Location); if new.Cost < Best_Planets(i).Cost Best_Planets(i) = new; end else % No Transit observed: Neighbouring planets Neighbor.Location = (rand().*Stars(i).Location + rand().*(unifrnd(Vmin,Vmax,1,nvar)))./2; for k = 1:SN zone = randi(3); if zone ==1 Neighbor.Location = Neighbor.Location - (2*rand()-1).*(unifrnd(Vmin,Vmax,1,nvar)); elseif zone ==2 Neighbor.Location = Neighbor.Location + (2*rand()-1).*(unifrnd(Vmin,Vmax,1,nvar)); else Neighbor.Location = Neighbor.Location + (2.*rand(1,nvar)-1).*(unifrnd(Vmin,Vmax,1,nvar)); end Neighbor.Location = max(Neighbor.Location, Vmin); Neighbor.Location = min(Neighbor.Location, Vmax); Neighbor.Cost = CostFunction (Neighbor.Location); SN_P(k) = Neighbor; end SUM = 0; for k = 1:SN SUM = SUM+SN_P(k).Location; end Neighbor.Location = SUM./SN; Neighbor.Cost = CostFunction (Neighbor.Location); if Neighbor.Cost < Best_Planets(i).Cost Best_Planets(i) = Neighbor; end end end %% Signal Amplification of the Best Planets (Exploitation) for i = 1:ns for k = 1:SN RAND = randi(2 ); if RAND ==1 Power = randi(SN*ns); Coefficient = 2*rand(); Noise = ((rand(1,nvar)).^Power).*(unifrnd(Vmin,Vmax,1,nvar)); else Power = randi(SN*ns); Coefficient = 2*rand(); Noise = -((rand(1,nvar)).^Power).*(unifrnd(Vmin,Vmax,1,nvar)); end % new.Location = (rand().*Best_Planets(i).Location) - Coefficient.*Noise; chance = randi(2); if chance ==1 new.Location = Best_Planets(i).Location - Coefficient.*Noise; else new.Location = (rand().*Best_Planets(i).Location) - Coefficient.*Noise; end