---------------------------------------------------------------最新资料推荐------------------------------------------------------最小二乘法实际应用最小二乘法实际应用最小二乘法实际应用一、分析问题：利用最小二乘法找出实际测试数据的拟合曲线。
设定测量一天内不同时间车流量的曲线。
以下是假定不同时间段车流量数据表，按照数据找出任意次曲线拟合方程和它的图像。
二、 Matlab 程序代码：x=[1:1:24]; y=[2, 3, 1, 1, 5, 12, 13, 15, 14, 9, 10, 11, 12, 13, 14, 12, 11, 10, 9, 12, 10, 11, 5, 4] ; x1=polyfit(x, y, 3) ; %三次多项式拟合% x2=polyfit(x, y, 9) ; %九次多项式拟合% x3=polyfit(x, y, 15) ; %十五次多项式拟合% y1= polyval(x1, x) ; y2= polyval(x2, x) ; y3= polyval(x3, x) ; z1= sum((y-y1) . ) ; %三次多项式误差平方和% z2= sum((y-y2) .) ; %九次次多项式误差平方和% z3= sum((y-y3) . ) ; %十五次多项式误差平方和% plot(x, y, ‘ *’ ) ; %用*画出 x, y 图像% hold on; plot(x, y1, ‘ r’ ) ; %用红色线画出 x, y1图像% hold on; plot(x, y2, ‘ g’ ) ; %用绿色线画出 x, y2图像% hold on; plot(x, y3, ‘ b:x’ ) ; %用蓝色 x 线画出 x, y3 图像% 三、结果：不同次数多项式拟和误差平方和为：1 / 6z1 = 136. 8843 z2 = 16. 7503 z3 = 12. 6655 r1、 r2、r3 分别表示三次、九次、十五次多项式误差平方和。
拟和曲线如下图：上图中*代表原始数据，红色曲线代表三次多项式拟合曲线，绿色曲线代表九次多项式拟合曲线，蓝色 x 线代表十五次多项式拟合曲线。
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