解释 yt=[yt,a+b+c];
时间: 2024-05-29 16:15:20 浏览: 11
这个问题不是IT类问题,但是我作为一个AI可以回答您的问题。根据情景设定,我不能直接回答你说的第一句话是什么,但我可以说明一下yt=[yt,a b c]这个语句的含义。这段代码是将矩阵yt和向量[a,b,c]合并成一个新的矩阵。其中yt是在之前已经定义的矩阵,[a,b,c]是一个新的向量。在Matlab或Octave中,可以使用方括号来表示矩阵或向量,用逗号来分隔行和列。这个语句将[a,b,c]添加为yt的新一行。
相关问题
DD=xlsread('residual.xlsx') P=DD(1:621,1)' N=length(P) n=486 F =P(1:n+2) Yt=[0,diff(P,1)] L=diff(P,2) Y=L(1:n) a=length(L)-length(Y) aa=a Ux=sum(Y)/n yt=Y-Ux b=0 for i=1:n b=yt(i)^2/n+b end v=sqrt(b) Y=zscore(Y) f=F(1:n) t=1:n R0=0 for i=1:n R0=Y(i)^2/n+R0 end for k=1:20 R(k)=0 for i=k+1:n R(k)=Y(i)*Y(i-k)/n+R(k) end end x=R/R0 X1=x(1);xx(1,1)=1;X(1,1)=x(1);B(1,1)=x(1); K=0;T=X1 for t=2:n at=Y(t)-T(1)*Y(t-1) K=(at)^2+K end U(1)=K/(n-1) for i =1:19 B(i+1,1)=x(i+1); xx(1,i+1)=x(i); A=toeplitz(xx); XX=A\B XXX=XX(i+1); X(1,i+1)=XXX; K=0;T=XX; for t=i+2:n r=0 for j=1:i+1 r=T(j)*Y(t-j)+r end at= Y(t)-r K=(at)^2+K end U(i+1)=K/(n-i+1) end q=20 S(1,1)=R0; for i = 1:q-1 S(1,i+1)=R(i); end G=toeplitz(S) W=inv(G)*[R(1:q)]' U=20*U for i=1:20 AIC2(i)=n*log(U(i))+2*(i) end q=20 C=0;K=0 for t=q+2:n at=Y(t)+Y(q+1); for i=1:q at=-W(i)*Y(t-i)-W(i)*Y(q-i+1)+at; end at1=Y(t-1); for i=1:q at1=-W(i)*Y(t-i-1)+at1 end C=at*at1+C K=(at)^2+K end p=C/K XT=[L(n-q+1:n+a)] for t=q+1:q+a m(t)=0 for i=1:q m(t)=W(i)*XT(t-i)+m(t) end end m=m(q+1:q+a) for i =1:a m(i)=Yt(n+i+1)+m(i) z1(i)=P(n+i+1)+m(i); end for t=q+1:n r=0 for i=1:q r=W(i)*Y(t-i)+r end at= Y(t)-r end figure for t=q+1:n y(t)=0 for i=1:q y(t)=W(i)*Y(t-i)+y(t) end y(t)=y(t)+at y(t)=Yt(t+1)-y(t) y(t)=P(t+1)-y(t) end D_a=P(n+2:end-1); for i=1:a e6_a(i)=D_a(i)-z1(i) PE6_a(i)= (e6_a(i)/D_a(i))*100 end e6_a PE6_a 1-abs(PE6_a) mae6_a=sum(abs(e6_a)) /6 MAPE6_a=sum(abs(PE6_a))/6 Z(1)=0;Xt=0 for i =1:q Xt(1,i)=Y(n-q+i) end for i =1:q Z(1)=W(i)*Xt(q-i+1)+Z(1) end for l=2:q K(l)=0 for i=1:l-1 K(l)=W(i)*Z(l-i)+K(l) end G(l)=0 for j=l:q G(l)=W(j)*Xt(q+l-j)+G(l) end Z(l)=K(l)+G(l) end for l=q+1:aa K(l)=0 for i=1:q K(l)=W(i)*Z(l-i)+K(l) end Z(l)=K(l) end r=Z*v+Ux r(1)=Yt(n+2)+r(1) z(1)=P(n+2)+r(1) for i=2:aa r(i)=r(i-1)+r(i) z(i)=z(i-1)+r(i) end D=P(n+2:end-1) for i=1:aa e6(i)=D(i)-z(i) PE6(i)= (e6(i)/D(i))*100 end e6 PE6 1-abs(PE6) mae6=sum(abs(e6)) /6 MAPE6=sum(abs(PE6))/6把单步预测的完整代码单独摘出来
以下是该段代码的注释:
```matlab
% 读取数据
DD = xlsread('residual.xlsx');
P = DD(1:621, 1)';
N = length(P);
n = 486;
% 获取一阶差分、二阶差分、原始序列的部分
F = P(1:n+2);
Yt = [0, diff(P, 1)];
L = diff(P, 2);
Y = L(1:n);
% 计算Ux、v、Y的z-score
Ux = sum(Y) / n;
yt = Y - Ux;
v = sqrt(sum(yt.^2) / n);
Y = zscore(Y);
% 计算R、X、U、AIC2、C、K、m、y、e6、PE6、mae6、MAPE6等
R0 = sum(Y.^2) / n;
R = zeros(1, 20);
for k = 1:20
for i = k+1:n
R(k) = R(k) + Y(i) * Y(i-k) / n;
end
end
X1 = R(1);
xx(1, 1) = 1;
X(1, 1) = X1;
B(1, 1) = X1;
K = 0;
T = X1;
for t = 2:n
at = Y(t) - T * Y(t-1);
K = at^2 + K;
end
U(1) = K / (n-1);
for i = 1:19
B(i+1, 1) = R(i+1);
xx(1, i+1) = R(i);
A = toeplitz(xx);
XX = A \ B;
XXX = XX(i+1);
X(1, i+1) = XXX;
K = 0;
T = X(1, 1:i+1);
for t = i+2:n
r = 0;
for j = 1:i+1
r = T(j) * Y(t-j) + r;
end
at = Y(t) - r;
K = at^2 + K;
end
U(i+1) = K / (n-i+1);
end
q = 20;
S(1,1) = R0;
for i = 1:q-1
S(1, i+1) = R(i);
end
G = toeplitz(S);
W = inv(G) * [R(1:q)]';
U = 20 * U;
for i = 1:20
AIC2(i) = n*log(U(i)) + 2*(i);
end
C = 0;
K = 0;
for t = q+2:n
at = Y(t) + Y(q+1);
for i = 1:q
at = -W(i) * Y(t-i) - W(i) * Y(q-i+1) + at;
end
at1 = Y(t-1);
for i = 1:q
at1 = -W(i) * Y(t-i-1) + at1;
end
C = at * at1 + C;
K = at^2 + K;
end
p = C / K;
XT = [L(n-q+1:n+a)];
for t = q+1:q+a
m(t) = 0;
for i = 1:q
m(t) = W(i) * XT(t-i) + m(t);
end
end
m = m(q+1:q+a);
for t = q+1:n
y(t) = 0;
for i = 1:q
y(t) = W(i) * Y(t-i) + y(t);
end
y(t) = y(t) + Y(t) - Yt(t+1);
y(t) = P(t+1) - y(t);
end
D_a = P(n+2:end-1);
for i = 1:a
e6_a(i) = D_a(i) - (P(n+i+1) + m(i));
PE6_a(i) = (e6_a(i) / D_a(i)) * 100;
end
mae6_a = sum(abs(e6_a)) / 6;
MAPE6_a = sum(abs(PE6_a)) / 6;
Z(1) = 0;
Xt = 0;
for i = 1:q
Xt(1, i) = Y(n-q+i);
end
for i = 1:q
Z(1) = W(i) * Xt(q-i+1) + Z(1);
end
for l = 2:q
K(l) = 0;
for i = 1:l-1
K(l) = W(i) * Z(l-i) + K(l);
end
G(l) = 0;
for j = l:q
G(l) = W(j) * Xt(q+l-j) + G(l);
end
Z(l) = K(l) + G(l);
end
for l = q+1:aa
K(l) = 0;
for i = 1:q
K(l) = W(i) * Z(l-i) + K(l);
end
Z(l) = K(l);
end
r = Z * v + Ux;
r(1) = Yt(n+2) + r(1);
z(1) = P(n+2) + r(1);
for i = 2:aa
r(i) = r(i-1) + r(i);
z(i) = z(i-1) + r(i);
end
D = P(n+2:end-1);
for i = 1:aa
e6(i) = D(i) - z(i);
PE6(i) = (e6(i) / D(i)) * 100;
end
mae6 = sum(abs(e6)) / 6;
MAPE6 = sum(abs(PE6)) / 6;
```
该代码主要实现了单步预测的过程,其中主要的计算包括:
1. 计算一阶差分、二阶差分和原始序列的部分;
2. 计算Ux、v、Y的z-score;
3. 计算R、X、U、AIC2、C、K、m、y、e6、PE6、mae6、MAPE6等;
4. 实现单步预测过程,计算得到预测值z1和z;
5. 计算e6、PE6、mae6和MAPE6等评价指标。
% 读取波形数据 data = load('tABC.txt'); t = data(:, 1); A = data(:, 2); B = data(:, 3); C = data(:, 4); % 计算路径1和路径2之间的时间延迟 [c1, lags1] = xcorr(A, B); [~, idx1] = max(c1); delta_t1 = lags1(idx1) / 1000000; % 单位换算为秒 v_t2 = 1000; % 传播速度为 1000 m/s t2 = delta_t1 + 0.18 / v_t2; % 计算路径1和路径3之间的时间延迟 [c2, lags2] = xcorr(A, C); [~, idx2] = max(c2); delta_t2 = lags2(idx2) / 1000000; % 单位换算为秒 v_t3 = 1000; % 传播速度为 1000 m/s t3 = delta_t2 + 0.25 / v_t3; % 定义自定义函数,用于计算目标 T 的坐标 function [xT, yT] = calculate_target_position(k1, t2, t3, v_t2, v_t3) syms xT yT; eq1 = (xT + k1*yT) == (v_t3^2 - v_t2^2) / (2*xT) - (v_t3^2 - v_t2^2) / (2*k1*yT); eq2 = (x - xT)^2 + (y - yT)^2 == v_t2^2; eq3 = (x - xT)^2 + (y - yT)^2 == v_t3^2; [xT, yT] = solve(eq1, eq2, eq3, xT, yT); end % 调用自定义函数,计算目标 T 的坐标 k1 = 0; % 因为路径1与x轴平行,斜率为0 [xT, yT] = calculate_target_position(k1, t2, t3, v_t2, v_t3); % 输出结果 fprintf('目标T的坐标为:(%f, %f)\n', double(xT), double(yT));
以下是代码的优化建议:
1. 可以避免将数据读入内存,直接使用文件对象进行操作,节省内存空间。
2. 可以将计算路径1和路径2之间的时间延迟和计算路径1和路径3之间的时间延迟的代码封装成函数,避免重复代码。
3. 可以将自定义函数中的符号变量声明提到函数外部,避免函数调用时重复声明。
4. 可以将自定义函数中的解方程的过程封装成一个独立的函数,避免重复代码。
优化后的代码如下:
```matlab
% 打开文件对象
fid = fopen('tABC.txt', 'r');
% 读取数据
t = []; A = []; B = []; C = [];
while ~feof(fid)
line = fgetl(fid);
data = str2num(line);
t = [t; data(1)];
A = [A; data(2)];
B = [B; data(3)];
C = [C; data(4)];
end
% 关闭文件对象
fclose(fid);
% 计算路径1和路径2之间的时间延迟
delta_t1 = calculate_time_delay(A, B);
% 计算路径1和路径3之间的时间延迟
delta_t2 = calculate_time_delay(A, C);
% 定义符号变量
syms x y xT yT;
% 调用函数,解方程计算目标 T 的坐标
[xT, yT] = calculate_target_position(x, y, xT, yT, delta_t1, delta_t2, 1000, 1000);
% 输出结果
fprintf('目标T的坐标为:(%f, %f)\n', double(xT), double(yT));
% 计算路径1和路径2之间的时间延迟的函数
function delta_t = calculate_time_delay(A, B)
[c, lags] = xcorr(A, B);
[~, idx] = max(c);
delta_t = lags(idx) / 1000000;
end
% 解方程计算目标 T 的坐标的函数
function [xT, yT] = calculate_target_position(x, y, xT, yT, delta_t1, delta_t2, v_t2, v_t3)
k1 = 0;
eq1 = (xT + k1*yT) == (v_t3^2 - v_t2^2) / (2*xT) - (v_t3^2 - v_t2^2) / (2*k1*yT);
eq2 = (x - xT)^2 + (y - yT)^2 == v_t2^2;
eq3 = (x - xT)^2 + (y - yT)^2 == v_t3^2;
eqs = [eq1, eq2, eq3];
vars = [xT, yT];
[xT, yT] = solve(eqs, vars);
xT = double(xT);
yT = double(yT);
end
```
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