Analysis and application of basketball sports characteristics based on intelligent optimization algorithm

As one of the sports with the highest overall popularity, basketball has attracted people's attention in various competitions. A basketball game needs players, coaches, referees, venues, high-definition video and other hardware facilities to organize together to complete. Through intelligent optimization algorithm, the data of players, coaches, referees and so on are analyzed. We need to get the offensive scoring method and defensive strategy suitable for a team, greatly increase the possibility of winning the game. This paper's experimental conclusions: (1) the traditional Ant Colony algorithm (AC) has the defects of complex calculation process and low calculation efficiency. Based on the investigation of experimental problems, the global optimization AC is obtained, which greatly improves the search speed and simplifies the search process. (2) through the analysis of the team's historical data by the intelligent optimization algorithm, the team's suitable offensive scoring method and the team (3) under the neural network greatly simplify the process, improve the concentration of regular training method, not only improve the training efficiency but also reduce unnecessary injuries.