1. Change the quadratic coefficient of the equation to 1. First, the quadratic coefficient is converted into 1 by dividing both sides by the quadratic coefficient. This can be achieved by moving the item or multiplying it by an appropriate number.

2. Move the constant term to the right of the equation. By adding the square of half the coefficient of the first term to both sides of the equation, the constant term moves to the right of the equation.

3. Complete the square. Write the left side of the equation as a complete square. This can be achieved by adding half the square of the coefficient of the first term to both sides.

4, the cure. Solving equations by radical operation. This can be achieved by using the definition of square root or a calculator.

Collocation method is a mathematical method for solving a quadratic equation with one variable, because it can transform the equation into a form that is easy to solve. However, it should be noted that the matching method is only applicable to real number solutions. If the quadratic coefficient is negative, or the equation has no real solution, then the matching method is not applicable.

Application of matching method in life;

1. financial investment: in portfolio theory, the matching method is used to optimize the portfolio. Allocating different assets according to their risks and expected returns can minimize the risks of the whole portfolio and maximize the expected returns.

2. Machine learning: In support vector machine (SVM) and other classification algorithms, the matching method is used to solve the quadratic optimization problem to maximize the classification interval. This can help us train a more accurate and powerful classifier.

3. Image processing: In digital image processing, the matching method is used to scale and rotate the image. For example, in image scaling, we can use matching method to adjust the width and height of the image to obtain the required size.

4. Computer vision: In computer vision, matching method is used for feature matching and image mosaic. By matching the feature points of different images and splicing them together, we can get a big picture containing multiple images.

5. Traffic planning: In traffic planning, the matching method is used to solve the optimal path problem. By using the matching method, we can find the shortest path from one place to another, or the best path to all places in a given time.

6. Medical imaging: In medical imaging, the matching method is used for image reconstruction. For example, in CT scanning, we can use matching method to reconstruct two-dimensional or three-dimensional images from projection data.