Progressive Conditional Generative Adversarial Network Optimized with Archimedes Optimization Algorithm Fostered Inheritance and Innovation of Huizhou Carving Culture

Abstract

Abstract The past dynasties literature has very few records as the literature of the earlier ones is a novelty and the hereditary secret historical and cultural assets are now at risk. In this study, the inheritance and innovation of the Huizhou carving culture using a progressive conditional generative adversarial network enhanced using the Archimedes Optimization algorithm (HCC-PCGAN-AO) is proposed. Initially, the data are gathered using the onsite Huizhou culture website with three-dimensional data scanning technique. The progressive conditional generative adversarial network (PCGAN) is used to design the Huizhou carving. Then, the Archimedes Optimization algorithm (AOA) is proposed to optimize the Progressive PCGAN classifier, which precisely eliminates errors in the design. It demonstrates the 3D digital carving into architectural cultural property is required and achieves a essential role in preserving the advancing architectural cultural heritage. The proposed HCC-PCGAN-AO method attains 22.13%, 19.46% and 30.65% lower RMSE compared with the existing methods such as Inheritance and Protection of Temple Architectural Cultural Heritage utilizing in the Case of Three-Mountain Kings Ancestral Temple of Jiexi Lintian with Digital Media Technology (IPTA-CH-DMT), Research on Innovative design of tourism cultural and creative products from the perception of Huizhou intangible cultural heritage culture (RID-TCC-HICHC) and Research on the Inheritance along Development of Huizhou Culture in the Construction of New Countryside in Anhui Province (RID-HCC-NCAP) respectively.

Keywords

• Archimedes optimization algorithm
• Huizhou carving culture
• Progressive conditional generative adversarial network
• Hereditary secret historical and cultural assets
• 3D digital carving