How to solve SIR model with using DTM (Differential Transform Method)
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I am trying to use dtm for solving SIR model, Although my code is run but I think the DTM part is wrong. I need help for DTM part
here is my code
function sir_model_dtm()
% Parameters
alpha = 0.3; % Infection rate
beta = 0.1; % Recovery rate
N = 1000; % Total population
I0 = 1; % Initial number of infected individuals
R0 = 0; % Initial number of recovered individuals
S0 = N - I0 - R0; % Initial number of susceptible individuals
% Time parameters
T = 100; % Total simulation time
dt = 1; % Time step
% Initialize arrays to store results
S = zeros(1, T);
I = zeros(1, T);
R = zeros(1, T);
% Initial conditions
S(1) = S0;
I(1) = I0;
R(1) = R0;
% Simulate the SIR model using DTM
for t = 2:T
% Compute new values
S(t) = S(t-1) - alpha*S(t-1)*I(t-1)/N * dt;
I(t) = I(t-1) + (alpha*S(t-1)*I(t-1)/N - beta*I(t-1)) * dt;
R(t) = R(t-1) + beta*I(t-1) * dt;
end
% Plot the results
t = 0:dt:T-dt;
plot(t, S, 'b', t, I, 'r', t, R, 'g', 'LineWidth', 2);
legend('Susceptible', 'Infectious', 'Recovered');
xlabel('Time');
ylabel('Number of individuals');
title('SIR Model');
end
2 件のコメント
Sam Chak
2024 年 4 月 17 日
Providing the mathematical formulas for Differential Transform Method would be helpful, as it saves users from having to search for it online.
回答 (1 件)
Athanasios Paraskevopoulos
2024 年 5 月 16 日
function sir_model_dtm()
% Parameters
alpha = 0.3; % Infection rate
beta = 0.1; % Recovery rate
N = 1000; % Total population
I0 = 1; % Initial number of infected individuals
R0 = 0; % Initial number of recovered individuals
S0 = N - I0 - R0; % Initial number of susceptible individuals
% Time parameters
T = 100; % Total simulation time
dt = 1; % Time step
% Initialize arrays to store results
S = zeros(1, T);
I = zeros(1, T);
R = zeros(1, T);
% Initial conditions
S(1) = S0;
I(1) = I0;
R(1) = R0;
% Simulate the SIR model using DTM
for t = 2:T
% Current values
S_curr = S(t-1);
I_curr = I(t-1);
R_curr = R(t-1);
% Compute intermediate values using DTM (predictor step)
S_inter = S_curr - alpha * S_curr * I_curr / N * dt;
I_inter = I_curr + (alpha * S_curr * I_curr / N - beta * I_curr) * dt;
R_inter = R_curr + beta * I_curr * dt;
% Compute new values (corrector step)
S(t) = S_curr - 0.5 * dt * (alpha * S_curr * I_curr / N + alpha * S_inter * I_inter / N);
I(t) = I_curr + 0.5 * dt * ((alpha * S_curr * I_curr / N - beta * I_curr) + (alpha * S_inter * I_inter / N - beta * I_inter));
R(t) = R_curr + 0.5 * dt * (beta * I_curr + beta * I_inter);
end
% Plot the results
t = 0:dt:T-dt;
plot(t, S, 'b', t, I, 'r', t, R, 'g', 'LineWidth', 2);
legend('Susceptible', 'Infectious', 'Recovered');
xlabel('Time');
ylabel('Number of individuals');
title('SIR Model');
end
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