Improved Bayesian Optimization Framework for Inverse Thermal Conductivity Based on Transient Plane Source Method.

In order to reduce the errors caused by the idealization of the conventional analytical model in the transient planar source (TPS) method, a finite element model that more closely represents the actual heat transfer process was constructed. The average error of the established model was controlled at below 1%, which was a significantly better result than for the analytical model, which had an average error of about 5%. Based on probabilistic optimization and heuristic optimization algorithms, an optimization model of the inverse heat transfer problem with partial thermal conductivity differential equation constraints was constructed. A Bayesian optimization algorithm with an adaptive initial population (BOAAIP) was proposed by analyzing the influencing factors of the Bayesian optimization algorithm upon inversion. The improved Bayesian optimization algorithm is not affected by the range and individuals of the initial population, and thus has better adaptability and stability. To further verify its superiority, the Bayesian optimization algorithm was compared with the genetic algorithm. The results show that the inversion accuracy of the two algorithms is around 3% when the thermal conductivity of the material is below 100 Wm-1K-1, and the calculation speed of the improved Bayesian optimization algorithm is three to four times faster than that of the genetic algorithm.

Application of Functional Training in Sports Dance Training.

With the rapid development of the economy, people's various needs for daily life are also increasing. Because this sport combines sports and dance, which makes the sport have the effect of physical fitness, as well as the emotional edification and visual beauty that dance brings to dancers and audiences. With the increase in people's needs, at the same time, corresponding to the relatively insufficient functional training of the project, this problem makes sports dance, the international standard ballroom dance, always at a low level of development, and at the same time, makes it lack of competitiveness. Also, the nature of dance is now more of a viewing experience. In view of the lack of functional training in international standard ballroom dancing, this article will study the role of functional training in this. By adopting the technology of human body feature recognition and functional action screening, it implements the steps of human action recognition detection technology, human action tracking technology, human body posture shape recognition method, and functional action screening. And the final experimental results show that functional training can screen out 57.3% of female dancers, with ligament damage, and 52.1% of male dancers. The screen outs were more than half of the total numbers, which shows that functional training effectively improves international standard ballroom dance that can provide good assistance for dancers' training.