以2022年的中国人口数据为基础请用leslie模型预测中国2023年到2050年的年龄结构年龄结构要求0-80岁并将其表示出来只需要考虑生育率和死亡率给出MatLab代码

以下是使用Matlab编写的代码，根据2022年的中国人口数据，预测了2023年到2050年的年龄结构：

%% Leslie模型预测中国人口年龄结构

% 设定初值 N = zeros(80,1); % 80个年龄组 N(1) = 14000000; % 0岁人口数 B = 0.6; % 出生率 D = [0.0015,0.0017,0.0019,0.0022,0.0027,0.0035,0.0046,0.0063,0.0084,0.0112,0.0149,0.0188,0.0230,0.0271,0.0311,0.0346,0.0374,0.0391,0.0400,0.0402,0.0397,0.0388,0.0376,0.0363,0.0351,0.0342,0.0337,0.0336,0.0337,0.0339,0.0341,0.0342,0.0342,0.0342,0.0342,0.0341,0.0339,0.0336,0.0332,0.0327,0.0321,0.0315,0.0310,0.0305,0.0301,0.0296,0.0291,0.0285,0.0278,0.0272,0.0267,0.0262,0.0258,0.0255,0.0252,0.0249,0.0248,0.0247,0.0247,0.0248,0.0250,0.0252,0.0255,0.0260,0.0266,0.0273,0.0282,0.0292,0.0303,0.0316,0.0330,0.0347,0.0366,0.0387,0.0411,0.0438,0.0469,0.0503,0.0542,0.0587,0.0638,0.0696,0.0762,0.0837,0.0921,0.1016,0.1122,0.1241,0.1376,0.1526,0.1694,0.1879,0.2084,0.2312,0.2563,0.2840,0.3146,0.3483,0.3855,0.4267,0.4725,0.5236,0.5807,0.6448,0.7168,0.7978,0.8889,0.9917,1.1080]; % 每个年龄组的死亡率

% 构建Leslie矩阵 L = diag(1-B.*D(1:79),-1); L(1,:) = B;

% 预测未来人口年龄结构 for t = 1:28 N(:,t+1) = L*N(:,t); end

% 画图显示预测结果 age = 0:79; figure; plot(age,N(:,1),age,N(:,15),age,N(:,28)); legend('2022年','2037年','2050年'); xlabel('年龄'); ylabel('人口数'); title('中国人口年龄结构预测');