#include <stdio.h> typedef struct { int year; float salary;} Data;int main(int argc, char* argv[]) { // Sample data Data sample_data[100]; printf("请输入样本数据的个数："); int sample_size; scanf("%d", &sample_size); printf("请依次输入样本数据的年份和平均工资：\n"); for (int i = 0; i < sample_size; i++) { scanf("%d%f", &sample_data[i].year, &sample_data[i].salary); } // 绘制散点图 FILE* gp = _popen("gnuplot -persist", "w"); fprintf(gp, "set title 'Average Salary of Graduates'\n"); fprintf(gp, "set xlabel 'Year'\n"); fprintf(gp, "set ylabel 'Salary'\n"); fprintf(gp, "plot '-' with points pointtype 6 pointsize 1.5 title 'Sample Data'\n"); for (int i = 0; i < sample_size; i++) { fprintf(gp, "%d %f\n", sample_data[i].year, sample_data[i].salary); } fprintf(gp, "e\n"); fflush(gp); // 使用最小二乘法拟合曲线 float sx = 0, sy = 0, sxx = 0, sxy = 0; for (int i = 0; i < sample_size; i++) { sx += sample_data[i].year; sy += sample_data[i].salary; sxx += sample_data[i].year * sample_data[i].year; sxy += sample_data[i].year * sample_data[i].salary; } float a = (sxy * sample_size - sx * sy) / (sxx * sample_size - sx * sx); float b = (sxx * sy - sx * sxy) / (sxx * sample_size - sx * sx); // 将拟合曲线绘制到散点图上 fprintf(gp, "set xrange [%d:%d]\n", sample_data[0].year, sample_data[sample_size - 1].year + 1); fprintf(gp, "f(x) = %f * x + %f\n", a, b); fprintf(gp, "plot '-' with points pointtype 6 pointsize 1.5 title 'Sample Data', f(x) with lines linewidth 2 title 'Fitted Curve'\n"); for (int i = 0; i < sample_size; i++) { fprintf(gp, "%d %f\n", sample_data[i].year, sample_data[i].salary); } fprintf(gp, "e\n"); fflush(gp); // 预测明年的平均工资 int next_year; float next_salary; printf("请输入要预测的年份："); scanf("%d", &next_year); next_salary = a * next_year + b; printf("预计 %d 年毕业生的平均工资是 %.2f\n", next_year, next_salary); return 0;}让这段代码最后拟合的曲线为二次函数以便于算出更精确的预测值

要将这段代码最后拟合的曲线改为二次函数，只需要将拟合公式中的一次函数改为二次函数即可。具体修改如下：

1. 将拟合公式中的一次函数 f(x) = a * x + b 改为二次函数 f(x) = ax^2 + bx + c。

2. 修改计算 a、b、c 的代码如下：

float sx = 0, sy = 0, sxx = 0, sxy = 0, sxxx = 0, sxxy = 0;
for (int i = 0; i < sample_size; i++) {
    sx += sample_data[i].year;
    sy += sample_data[i].salary;
    sxx += sample_data[i].year * sample_data[i].year;
    sxy += sample_data[i].year * sample_data[i].salary;
    sxxx += sample_data[i].year * sample_data[i].year * sample_data[i].year;
    sxxy += sample_data[i].year * sample_data[i].year * sample_data[i].salary;
}
float det = sxx * sxx * sample_size - 2 * sx * sxx * sx + sx * sx * sxxx + sample_size * sx * sx * sxx - sample_size * sxx * sxx;
float a = (sx * sxx * sy - sx * sxy * sx - sxx * sxx * sy + sxx * sxxy * sample_size + sxx * sxy - sx * sxxx * sample_size) / det;
float b = (-sx * sxx * sx * sy + sx * sx * sxxx * sy + sxx * sxx * sxy - sxx * sx * sxxy - sxx * sx * sy + sx * sxx * sxxy) / det;
float c = (sxx * sx * sxy - sx * sx * sxx * sy - sxx * sxx * sxxy + sx * sxxx * sxy + sx * sxx * sy - sx * sxx * sxxy) / det;

3. 将绘制拟合曲线的代码修改为：

fprintf(gp, "set xrange [%d:%d]\n", sample_data[0].year, sample_data[sample_size - 1].year + 1);
fprintf(gp, "f(x) = %f * x**2 + %f * x + %f\n", a, b, c);
fprintf(gp, "plot '-' with points pointtype 6 pointsize 1.5 title 'Sample Data', f(x) with lines linewidth 2 title 'Fitted Curve'\n");

这样就可以将拟合曲线改为二次函数，从而得到更精确的预测值。