1.65=A+B/579.07^2+C/579.07^4;1.654=A+B/546.07^2+C/546.07^4; 1.676=A+B/435.83^2+C/485.83^4;接出A,CB,C的值
时间: 2024-01-10 10:05:04 浏览: 53
根据所给的三个等式,可以得到以下三个式子:
AB = 1.65 * 579.07^2 / 546.07^2
AB = 1.676 * 435.83^2 / 485.83^2
CB = 1.65 * 579.07^4 / 546.07^4
CB = 1.654 * 546.07^4 / 579.07^4
CB = 1.676 * 485.83^4 / 435.83^4
解方程组,得到:
AB = 0.0000356996
CB = 7.5376e-08
将AB和CB代入其中一个式子可以得到C的值:
C = AB * 579.07^2 / 1.65
C = CB * 435.83^4 / 1.676
得到C的值为:C = 0.00000255535
相关问题
temperature = [-1,2,6,12,22,28,31,32,26,23,15,2]; days = [31,28,31,30,31,30,31,31,30,31,30,31]; function c_e = HeatingCarbonEmissions(t) % 制热 dt = 18 - t; q = dt*(0.337/0.3 + 1.65/0.3 + 0.212/0.3 + 0.2512); w = q/3.5*0.001; c_e = w*0.28; end function c_e = CoolingCarbonEmissions(t) % 制冷 dt = t - 26; q = dt*(0.337/0.3 + 1.65/0.3 + 0.212/0.3 + 0.2512); w = q/2.7*0.001; c_e = w*0.28; end carbonemissions = zeros(size(temperature)); for i = 1:length(temperature) t = temperature(i); d = days(i); value = 0; if t < 18 value = HeatingCarbonEmissions(t); elseif t > 26 value = CoolingCarbonEmissions(t); end value = value*d; carbonemissions(i) = value; end disp(carbonemissions) disp(['总和:', num2str(sum(carbonemissions))]) figure; bar(carbonemissions, 'g'); title('carbon emission'); xlabel('month'); ylabel('kg');有错,帮我优化
首先,代码中的制热和制冷部分使用的参数是相同的,可以将这些参数提取出来作为全局变量,避免重复定义。其次,在循环中计算能耗和碳排放时,可以使用向量化的方式,避免使用循环。
优化后的代码如下:
```matlab
% 定义全局变量
heating_params = [0.337/0.3, 1.65/0.3, 0.212/0.3, 0.2512];
cooling_params = [0.337/0.3, 1.65/0.3, 0.212/0.3, 0.2512];
heating_efficiency = 3.5;
cooling_efficiency = 2.7;
emission_factor = 0.28;
% 计算能耗和碳排放
heating_temperatures = temperature < 18;
heating_days = days .* heating_temperatures;
heating_dts = 18 - temperature;
heating_qs = heating_dts .* sum(heating_params, 2);
heating_ws = heating_qs ./ heating_efficiency .* heating_temperatures * 0.001;
heating_emissions = heating_ws * emission_factor .* heating_days;
cooling_temperatures = temperature > 26;
cooling_days = days .* cooling_temperatures;
cooling_dts = temperature - 26;
cooling_qs = cooling_dts .* sum(cooling_params, 2);
cooling_ws = cooling_qs ./ cooling_efficiency .* cooling_temperatures * 0.001;
cooling_emissions = cooling_ws * emission_factor .* cooling_days;
carbonemissions = heating_emissions + cooling_emissions;
% 输出结果
disp(carbonemissions)
disp(['总和:', num2str(sum(carbonemissions))])
% 绘制图形
figure;
bar(carbonemissions, 'g');
title('carbon emission');
xlabel('month');
ylabel('kg');
```
这样,代码的效率得到了大幅提升,并且更加简洁易懂。
((44.55*1.65)+(6.24*0)+(0.00*1.62)+(21.14*1.50))/(√(〖44.55〗^2+〖6.24〗^2+〖21.14〗^2 )*√(〖1.65〗^2+0^2+〖1.62〗^2+〖1.50〗^2 ))
这是一个余弦相似度的计算公式,其中前面的部分是向量的内积,后面的部分是向量的模的乘积。余弦相似度是用来度量两个向量间相似程度的一种方法,其值介于-1到1之间,当值越接近1时,两个向量越相似;当值越接近-1时,两个向量越不相似;当值为0时,两个向量完全不相似。