mademo.m

时间序列预测算法。支持5种常见的算法 移动平均 非线性回归 指数平滑等

function mademo
% ma预测

% Parameter：
nseq = [105851 107507 109300 111026 112704 114333 115823 117171 118517 ...
    119850 121121 122389 123626 124761 125786 126743 127627 128453 129227 129988 130756 131448 132129];

% Base the Input Predict Method to solve the nseq
n = 15;
for j = 1: 1: n
    yfilter(j) = nseq(j);
    yfilter(j) = nseq(j);
    yfilter(j) = nseq(j);
end

for i = 16 : 1: length(nseq)
    yfilter(i) = (nseq(i) + yfilter(i-1) + yfilter(i-2) + yfilter(i-3) + ...
        yfilter(i-4) + yfilter(i-5) + yfilter(i-6) + yfilter(i-7) + yfilter(i-8) + ...
        + yfilter(i-9) + yfilter(i-10) + yfilter(i-11) + yfilter(i-12) + yfilter(i-13) + ...
        + yfilter(i-n+1)) /n;
end

% Plot the orignal Graphic
x = 1:8;    % 10个标本数据
y = nseq(16:23);
plot(x,y, '--b*',x,yfilter(16:23), '--rs','LineWidth',2,...
                'MarkerEdgeColor','k',...
                'MarkerFaceColor','g',...
                'MarkerSize',2);

mse = MSE(nseq(16:23), yfilter(16:23));
avmae = mae(nseq(16:23), yfilter(16:23));
rerr = releaterror(nseq(16:23), yfilter(16:23));
disp( sprintf('The mean square error is: %f', mse ));
disp( sprintf('The  avarage real error is: %f', avmae ));
disp( sprintf('平均相对误差 is %f', rerr));
title('全社会客货运输量移动平均模型预测', 'FontSize', 10);
xlabel('月份', 'FontSize', 10);
ylabel('铁路客户量(亿)', 'FontSize', 10);
grid on