SEIR.zip_SEIR模型 MATLAB_SEIR模型图像_seir模型 网页_seir模型c++_seir模型网站

time=[0:0.01:20]; %suppose in days k = 20; ke = 0.8; % average degree of educated individuals (using social media to communication) % suppose it's number of people may see the rumor through social media in a day ku = 0.7; % average degree of uneducated individuals (person-to-person communication % suppose it's number of people may hear the rumor through direct communication lambda = 0.6; %probability of people in educated group disseminates rumor and change into spreader %probability of people in uneducated group disseminates rumor and change into spreader %probability of people in educated group that may doubt the creadibility of rumor gamma = 0.1; %probability of people in uneducated group that may doubt the creadibility of rumor %probability of people in educated group that change into stifler when contact a stifler eta = 0.5; %probability of people in educated group that change into stifler when contact a stifler delta = 0.9; %probability of people that lose interest or forget about rumor beita = 0.3; beita2 = 0.1; N = 37289406; %Sudan population: http://en.wikipedia.org/wiki/List_of_countries_by_population pe = 0.21; %Sudan Internet users:http://en.wikipedia.org/wiki/List_of_countries_by_number_of_Internet_users pu = 0.79; YInit=[(pe*N-1)/N (pu*N-1)/N 0 1/N 0]; options=[ ]; [t,PredY]=ode45(@SEIRR, time,YInit, options,k,ke, ku, lambda, delta , gamma, eta,beita,beita2); %digits(15) %vpa(N*PredY) PredIr = PredY(:,1); PredIs = PredY(:,2); PredE = PredY(:,3); %PredSu = PredY(:,4); PredS = PredY(:,4); PredR = PredY(:,5); figure; plot(t, PredIr, t, PredIs, t,PredE,t,PredS,t,PredR) %plot(t, PredIe, t, PredIu) %plot(t,PredSe, t, PredSu) %plot(t, PredR) ylabel('Probability') xlabel('Time') legend('Ir ', 'Is' , 'E', 'S ','R') %legend('Educated Ignorant ', 'Uneducated Ignorant') %legend('Educated Spreaders ', 'Uneducated Spreaders ') %legend('Stiflers') title('SEIR model') axis([0 20 -0.15 1.15]) %changing delta 相关性 %{ delta1 = 0.02; delta2 = 0.08; delta3 = 0.15; delta4 = 0.45; delta5 = 0.80; [t,PredY1]=ode45(@SEIRR, time,YInit, options, k,ke, ku, lambda, delta1, gamma, eta,beita,beita2); [t,PredY2]=ode45(@SEIRR, time,YInit, options, k,ke, ku, lambda, delta2, gamma, eta,beita,beita2); [t,PredY3]=ode45(@SEIRR, time,YInit, options, k,ke, ku, lambda, delta3, gamma, eta,beita,beita2); [t,PredY4]=ode45(@SEIRR, time,YInit, options, k,ke, ku, lambda, delta4, gamma, eta,beita,beita2); [t,PredY5]=ode45(@SEIRR, time,YInit, options, k,ke, ku, lambda, delta5, gamma, eta,beita,beita2); PredIr1 = PredY1(:,1); PredIs1 = PredY1(:,2); PredE1 = PredY1(:,3); PredS1 = PredY1(:,4); PredR1 = PredY1(:,5); PredIr2 = PredY2(:,1); PredIs2 = PredY2(:,2); PredE2 = PredY2(:,3); PredS2 = PredY2(:,4); PredR2 = PredY2(:,5); PredIr3 = PredY3(:,1); PredIs3 = PredY3(:,2); PredE3 = PredY3(:,3); PredS3 = PredY3(:,4); PredR3 = PredY3(:,5); PredIr4 = PredY4(:,1); PredIs4 = PredY4(:,2); PredE4 = PredY4(:,3); PredS4 = PredY4(:,4); PredR4 = PredY4(:,5); PredIr5 = PredY5(:,1); PredIs5 = PredY5(:,2); PredE5 = PredY5(:,3); PredS5 = PredY5(:,4); PredR5 = PredY5(:,5); figure; plot(t, PredIr1, t, PredIr2, t, PredIr3, t, PredIr4, t, PredIr5) ylabel('Probability') xlabel('Time') legend('\mu = 0.02', '\mu = 0.08', '\mu = 0.15', '\mu = 0.45', '\mu = 0.80') title('Ir - Changing \mu') axis([0 20 0 0.25]) figure; plot(t, PredIs1, t, PredIs2, t, PredIs3, t, PredIs4, t, PredIs5) ylabel('Probability') xlabel('Time') legend('\mu = 0.02', '\mu = 0.08', '\mu = 0.15', '\mu = 0.45', '\mu = 0.80') title('Is - \mu') axis([0 20 -0.15 1]) figure; plot(t, PredE1, t, PredE2, t, PredE3, t, PredE4, t, PredE5) ylabel('Probability') xlabel('Time') legend('\mu = 0.02', '\mu = 0.08', '\mu = 0.15', '\mu = 0.45', '\mu = 0.80') title('e - \mu') axis([0 20 -0.01 0.9]) figure; plot(t, PredS1, t, PredS2, t, PredS3, t, PredS4, t, PredS5) ylabel('Probability') xlabel('Time') legend('\mu = 0.02', '\mu = 0.08', '\mu = 0.15', '\mu = 0.45', '\mu = 0.80') title('S - \mu') axis([0 20 -0.01 1]) figure; plot(t, PredR1, t, PredR2, t, PredR3, t, PredR4, t, PredR5) ylabel('Probability') xlabel('Time') legend('\mu = 0.02', '\mu = 0.08', '\mu = 0.15', '\mu = 0.45', '\mu = 0.80') title('R - \mu') axis([0 20 -0.05 1]) %{ figure; plot(t, PredR1, t, PredR2, t, PredR3, t, PredR4, t, PredR5) ylabel('Probability') xlabel('Time') legend('\delta = 0.02', '\delta = 0.08', '\delta = 0.15', '\delta = 0.45', '\delta = 0.80') title('Stiflers - Changing probability of people that lose interest or forget about rumor') axis([0 10 -0.15 1.15]) %} %} lamda1 = 0.1; lamda2 = 0.5; lamda3 = 0.7; [t,PredY1]=ode45(@SEIRR, time,YInit, options, k,ke, ku, lamda1, delta, gamma, eta,beita,beita2); [t,PredY2]=ode45(@SEIRR, time,YInit, options, k,ke, ku, lamda2, delta, gamma, eta,beita,beita2); [t,PredY3]=ode45(@SEIRR, time,YInit, options, k,ke, ku, lamda3, delta, gamma, eta,beita,beita2); PredIr1 = PredY1(:,1); PredIs1 = PredY1(:,2); PredE1 = PredY1(:,3); PredS1 = PredY1(:,4); PredR1 = PredY1(:,5); PredIr2 = PredY2(:,1); PredIs2 = PredY2(:,2); PredE2 = PredY2(:,3); PredS2 = PredY2(:,4); PredR2 = PredY2(:,5); PredIr3 = PredY3(:,1); PredIs3 = PredY3(:,2); PredE3 = PredY3(:,3); PredS3 = PredY3(:,4); PredR3 = PredY3(:,5); figure; plot(t, PredIr1, t, PredIr2, t, PredIr3) ylabel('Probability') xlabel('Time') legend('\lambda = 0.1', '\lambda = 0.5', '\lambda = 0.7') title('Ir - Changing \lambda') axis([0 20 0 0.25]) figure; plot(t, PredIs1, t, PredIs2, t, PredIs3) ylabel('Probability') xlabel('Time') legend('\lambda = 0.1', '\lambda = 0.5', '\lambda = 0.7') title('Is - \lambda') axis([0 20 -0.15 1]) figure; plot(t, PredE1, t, PredE2, t, PredE3) ylabel('Probability') xlabel('Time') legend('\lambda = 0.1', '\lambda = 0.5', '\lambda = 0.7') title('e - \lambda') axis([0 20 -0.01 0.9]) figure; plot(t, PredS1, t, PredS2, t, PredS3) ylabel('Probability') xlabel('Time') legend('\lambda = 0.1', '\lambda = 0.5', '\lambda = 0.7') title('S - \lambda') axis([0 20 -0.01 1]) figure; plot(t, PredR1, t, PredR2, t, PredR3) ylabel('Probability') xlabel('Time') legend('\lambda = 0.1', '\lambda = 0.5', '\lambda = 0.7') title('R - \lambda') axis([0 20 -0.05 1])