What is gray forecast?
The gray forecasting model is a forecasting method that establishes a mathematical model to make forecasts through a small amount of incomplete information. It is based on the past and present development laws of objective things, with the help of scientific methods to describe and analyze future development trends and conditions, and form scientific assumptions and judgments.
Advantages, disadvantages and scope of application of the gray forecasting model:
Applicability: The model uses not a sequence of raw data, but a sequence of generated data. The core system is Gray Model, which is a method of accumulating raw data (or other processing to generate) to obtain an approximate exponential law and then modeling.
Advantages: When dealing with less eigenvalue data, the data sample space does not need to be large enough to solve the problems of less historical data, sequence integrity and low reliability, and can generate irregular original data to obtain regular Strong generating sequence.
Disadvantages: It is only suitable for short-term and medium-term forecasts, and only suitable for forecasts that approximate exponential growth.
The gray prediction code (matlab) is as follows:
%Matlab的灰色预测程序：
%y=input('请输入数据');
clc;clear
y=[29.8 30.11 41.05 70.12 77.79 77.79 104.82 65.22 82.7 100.79]
n=length(y);
yy=ones(n,1);
yy(1)=y(1);
for i=2:n
yy(i)=yy(i-1)+y(i)
end
B=ones(n-1,2);
for i=1:(n-1)
B(i,1)=-(yy(i)+yy(i+1))/2;
B(i,2)=1;
end
BT=B';
for j=1:(n-1)
YN(j)=y(j+1);
end
YN=YN';
A=inv(BT*B)*BT*YN;
a=A(1);
u=A(2);
t=u/a;
t_test=input('输入需要预测的个数');
i=1:t_test+n;
yys(i+1)=(y(1)-t).*exp(-a.*i)+t;
yys(1)=y(1);
for j=n+t_test:-1:2
ys(j)=yys(j)-yys(j-1);
end
x=1:n;
xs=2:n+t_test;
yn=ys(2:n+t_test);
plot(x,y,'^r',xs,yn,'*-b');
det=0;
for i=2:n
det=det+abs(yn(i)-y(i));
end
det=det/(n-1);
disp(['百分绝对误差为：',num2str(det),'%']);
disp(['预测值为：',num2str(ys(n+1:n+t_test))]);
%请输入数据 [29.8 30.11 41.05 70.12 77.79 77.79 104.82 65.22 82.7 100.79]