Meisai experience sharing
In general, my experience is:
1. Before the competition, be diligent and practice! Remember that there is a great Matlab in your computer (you can replace it with VS, SPSS and other software). Practice is the best teacher. If you are not familiar with Matlab, you must type more code, especially to exercise drawing ability. Teachers read an article. The first thing that produces a visual impact is whether your drawing is good, not your algorithm. Not awesome. Therefore, the relevant code required for drawing should be typed skillfully. For example, you can use Matlab to type the questions previously typed in C language, and type the complicated calculations again with Matlab. As for myself, when I usually do professional homework, I often use Matlab for iterative calculations and drawing. This kind of similar homework is available in all majors. For example, I am a port and shipping professional to move bricks, and there are many problems that can be solved with a computer. Slowly you will improve.
2. During the game, you must learn to be lazy! During the game, you can not type the code yourself, don't type it yourself (note that I am talking about the game. Of course, the more you practice, the better). For most of the model questions, the basic algorithms used are definitely ready-made. If you have worked hard to type the things that the predecessors have typed, you will have to try again and again. The competition will only take three days, a waste of time! Understand the idea of the algorithm, understand the meaning of the code, know what topics can be used, and how to modify the algorithm. So if time is tight, you must collect more common algorithm codes. I used the code in the link above when I was competing.
3. The focus of the award is on the existing algorithm, how to innovate, how to add and the unusual things of the basic algorithm. Innovation is an absolute point. Our group basically didn't refer to a few articles at the time. The basic model was built by itself, and many correction conditions were added when referring to other people's models. Some basic algorithms were used in the model solving. I won the prize unexpectedly, wow haha. Oh yes, and the pictures must be beautiful!