Research on Computer Intelligent Simulation System of Ceramic Art Creation Process Based on Deep Learning

This study proposes an intelligent simulation system of ceramic art creation process based on deep learning. The system models and simulates each link of ceramic art creation through a deep neural network model, covering the entire process from clay molding to finished product firing, aiming to accurately reproduce the complexity and details of ceramic art creation in a virtual environment. The core of the system adopts a method combining CNN and RNN, and through large-scale ceramic art data training, the model can generate highly realistic ceramic art works. In the data preprocessing stage, the system normalizes key variables such as soil humidity, rotation speed, and molding temperature, and improves the diversity of training data through data enhancement methods. Through comparative experiments with traditional ceramic art creation methods, the results show that the system can significantly improve the creation efficiency and optimize the quality of ceramic art works. The simulation results show that under different parameter settings, the system can generate ceramic art works that meet expectations. For example, when the humidity is controlled at 50% and the rotation speed is 300rpm, the surface smoothness of the ceramic art works generated by the model is improved by 18.4%, and the molding accuracy is improved by 12.7<sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">%</sup>.