price_n_a[4] = 87.67;

       bar_num_a[4] = 68;

       zcl_lsm(bar_num_a,price_n_a,Slope_n,Intercept_n);

   }

   OnBar(ArrayRef<Integer> indexs)

   {

       PlotString("CurrentBar",Text(CurrentBar) + ":" + text(h,2),h,Yellow);

       Commentary("斜率:" + text(Slope_n,1) + " 截距:" + text(Intercept_n));

       zuiyoujie_n_se = Slope_n * CurrentBar + Intercept_n;

       PlotNumeric("线性规划",zuiyoujie_n_se,zuiyoujie_n_se,White);

   }

老师真厉害

这就是最简单的线性规划 啥时候搞出来 神经网络 机器学习 深度学习的算法 那才牛

Defs

Events

   OnInit()

   {

       SetArraySize(price_n_a, 5, 0);

       SetArraySize(bar_num_a, 5, 0);

       price_n_a[0] = 78.46;

       bar_num_a[0] = 191;

       price_n_a[1] = 72.88;

       bar_num_a[1] = 213;

       price_n_a[2] = 71.51;

       bar_num_a[2] = 224;

       price_n_a[3] = 84.52;

       bar_num_a[3] = 125;

//------------------------------------------------------------------------

// 简称: testlsm

// 名称:

// 类别: 策略应用

// 类型: 用户应用

// 输出: Void

//------------------------------------------------------------------------

Params

   //此处添加参数

Vars

   //此处添加变量

   Series<Numeric> zuiyoujie_n_se;

   Array<Numeric> price_n_a;

   Array<Numeric> bar_num_a;

   Global Numeric Slope_n;

   Global Numeric Intercept_n;

输入图中画圆圈的5个点的数值，得出来的白色的拟合线，还算过关吧

 //算出斜率

   Slope_n_ref = (arrSize_n * sum_xy_n - sum_x_n * sum_y_n) /temp;

   //截距

   Intercept_n_ref = (sum_y_n * sum_xx_n - sum_x_n * sum_xy_n) / temp;

   Return 1;

End

Begin

   arrSize_n = GetArraySize(arr_X);

   if(arrSize_n<2)

   {

       Return 0;

   }

   sum_x_n = 0;

   sum_y_n = 0;

   sum_xy_n = 0;

   sum_xx_n = 0;

   Numeric i ;

   for i = 0 to arrSize_n - 1

   {

       sum_x_n = sum_x_n + arr_X[i];

       sum_y_n = sum_y_n + arr_Y[i];

       sum_xx_n = sum_xx_n + arr_X[i] * arr_X[i];

       sum_xy_n = sum_xy_n + arr_X[i] * arr_Y[i];

   }

   temp = arrSize_n * sum_xx_n - sum_x_n * sum_x_n;

免费

Params

   Arrayref<Numeric> arr_X;    //数值型数组

   Arrayref<Numeric> arr_Y;    //数值型数组

   NumericRef Slope_n_ref;//斜率

   NumericRef Intercept_n_ref;//截距

Vars

   Numeric arrSize_n;

   Numeric sum_x_n(0);

   Numeric sum_y_n(0);

   Numeric sum_xx_n(0);

   Numeric sum_xy_n(0);

int main() {

   DataPoint dataPoints[] = {{1, 1}, {2, 2}, {3, 5}, {4, 4}, {5, 3}};

   int numPoints = sizeof(dataPoints) / sizeof(dataPoints[0]);

   double slope = calculateSlope(dataPoints, numPoints);

   double intercept = calculateIntercept(dataPoints, numPoints, slope);

   printf("最佳拟合直线方程：y = %.2f * x + %.2f\n", slope, intercept);

   return 0;

}

double calculateIntercept(DataPoint *points, int count, double slope) {

   double sumY = 0, sumXY = 0;

   for (int i = 0; i < count; i++) {

       sumY += points[i].y;

       sumXY += points[i].x * points[i].y;

   }

   double intercept = (sumY - slope * sumX) / count;

   return intercept;

}

double calculateSlope(DataPoint *points, int count) {
    double sumX = 0, sumY = 0, sumXY = 0, sumXX = 0;
    for (int i = 0; i < count; i++) {
        sumX += points[i].x;
        sumY += points[i].y;
        sumXY += points[i].x * points[i].y;
        sumXX += points[i].x * points[i].x;
    }
    double slope = (count * sumXY - sumX * sumY) / (count * sumXX - sumX * sumX);
    return slope;
}