A machine learning approach to modelling and simulating the behaviour of systems with deformable particles

The paper presents an approach to model and simulate a discrete system with deformable particles. The observed system is represented and considered as a system with concentrated parameters (particles) connected by elastic springs and damping. The system model thus created is used for learning the graphical neural network, which we intend to use to obtain the results of the simulation with less CPU power. The mathematical model of this system was implemented by creating a computer solution using the Java programming language and the OpenGL 3D graphics standard. Using this model, the problem analysis was performed and the simulation results are presented graphically.