Research on optimization of teaching mental health monitoring and evaluation system based on intelligent algorithm

Abstract

Abstract Recently, the application and optimization research of intelligent algorithms in the monitoring and evaluation system of teaching mental health has been focused on. Many countries cannot avoid that with the rapid development of the urban economy, the mental health of Chinese people is ignored without knowing it. This phenomenon is more obvious in today’s campuses, especially in colleges and universities. Although the campus is equipped with a psychological counseling office, most students choose to give up because they can’t face themselves in a bad mood. Traditional random checks and individual conversations have no good effect. The intelligent algorithm developed in the new era is inevitably applied to the detection and evaluation of teaching psychological health. However, the intelligent algorithm at this stage cannot meet the requirements of teaching mental health monitoring and evaluation, because the data collection and processing are not completed through the matching intelligent algorithm, but directly through the algorithm DC method. The data collection will cause certain errors, and the data processing and output will inevitably be biased. This research is a kind of optimized intelligent algorithm system that can be applied to the monitoring and evaluation of teaching mental health. First, the research introduces and compares several modern intelligent algorithms used in teaching mental health monitoring and evaluation, and then analyzes the main influencing factors of monitoring and evaluation. These factors are integrated into the intelligent algorithm monitoring and evaluation system as key intelligent algorithm research objects, Finally, the optimized monitoring and evaluation system is applied in practice to obtain the corresponding imperfect information performance, and the final optimized result is obtained through further improvement. The results show that in most cases, a certain intelligent algorithm can not fully adapt to the detection and evaluation system, but the combination of different kinds of intelligent algorithms through influencing factors can give play to its advantages, and the final results can also be consistent with the actual. The proposed intelligent algorithm can not only be used in the monitoring and evaluation of teaching mental health but also reflect more monitoring and evaluation of teaching quality. The essence of the intelligent algorithm is to obtain complete data that can reflect reality by exploring the value of various information data. In the future, more joint intelligent algorithms will be proposed, which can adapt to more situations and achieve complete applications in teaching, security, medicine, and other fields.