Construction and Analysis of Employment Structure System Based on Artificial Intelligence and Its Influencing Factors

The construction of an employment structure system is an indispensable part of achieving modernization in Chinese education. Improving the scientific nature, rationality, and timeliness of evaluating this system plays a critical role. Compared to traditional genetic algorithms, an adaptive mutation method has been proposed in the process of optimizing the employment structure. The improvement involves finding the global optimal solution among different evaluation indicator systems for employment through a mutation operation process. An adaptive mutation probability is adopted, meaning that when the population obtains different fitness values, appropriate mutation probabilities are used at different times. This approach aims to increase or decrease population diversity and the number of superior individuals as needed, thereby enhancing the genetic algorithm’s ability to search for the global optimal solution. The results show that the employment structure evaluation system can achieve optimized assessment and objectively reflect the overall employment situation.