1:50 PM - 2:10 PM
[3K1-OS-18a-01] High-Speed Calculation in Structural Analysis by Reinforcement Learning
Keywords:Machine Learning, Numerical Analysis
By improvement of computer’s performance, it has become to enable to simulate the behavior of structure, soil and so on using the nonlinear structural analysis of large and complex models. However, these simulations require lots number of convergent calculation to search a convergent solution. Although there are several convergent methods such as Newton’s method, there is no almighty method that fits all situations. Hence, it is up to the person carrying out the analysis to select one of these methods. Considering this situation, in this paper, we propose a method to choose and combine the appropriate convergent method using the concept of Q-learning from reinforcement learning. First, using simple analysis model, we train an action value table to choose the appropriate convergent method with Q-learning. Then, we carried out an analysis using obtained action value table and show that our method can make the convergence time shorter than conventional ones.