Artificial neural network and its application in ceramic technology level identification

To enhance the performance and technological sophistication of ceramic products, this study integrates artificial neural network techniques to develop a system for identifying the technological grade of ceramics, employing advanced ceramic image recognition methods to assess and validate the quality level of the products. Moreover, the numerical calculation program of the physical quantity of Mie scattering theory is written on the MATLAB software to analyze the numerical value of scattering series of ceramic craft products, the relationship between scattering coefficient and particle size, and the relationship between scattered light flux and particle size. In addition, this paper conducts graph analysis to study and understand the properties of Mie scattering theory more deeply. Finally, the image algorithm is applied to construct the system. Simulation results indicate that the ceramic technology level identification and processing system, developed using artificial neural network techniques, effectively supports the manufacturing and classification of contemporary ceramic products.