Cross-Cultural Examination of Intelligent Perception and Group Intention in Ceramic Appreciation Analysis

Ceramics have a critical position in the history of world cultural development and are the crystallization of art and science. As we all know, the development of Chinese ceramics has a long history and is representative of the primitive culture of the Chinese nation. Determining the source and dating of unearthed ceramics is essential in current archaeological work. With the combination of science and technology and archaeological research, the technical analysis of ceramic appreciation has gradually increased. At present, the research work on ancient ceramics in China mainly focuses on the determination of their composition and element content. This paper uses appropriate multivariate statistical methods to analyze ancient ceramics' chemical composition determination data. It proposes a ceramic intelligence method based on principal component analysis (PCA) and BP neural networks. A neural network parameter-while-drilling ceramic intelligent perception model; then, three different ceramic "three-in-one" rock samples were simulated through similar materials, and the unique ceramic manufacturing process was used to enter the test bench to obtain the drilling speed, rotation speed, and drilling pressure of the drilling rig, slewing pressure, slewing torque, mud pump pressure. And other six parameters while drilling. Finally, the theoretical model is trained and tested. The results demonstrate that compared with the traditional BP neural network ceramic intelligent perception model, the PCA-BP neural network ceramic brilliant perception method reduces the model calculation amount, and the accuracy of ceramic intellectual perception has been effectively improved. © 2024 U-turn Press LLC.