RETRACTED ARTICLE: A novel architecture design for artificial intelligence-assisted culture conservation management system

Ziqi Zhou; Ziqi Zhou

doi:10.3934/mbe.2023425

Mathematical Biosciences and Engineering

2023, Volume 20, Issue 6: 9693-9711. doi: 10.3934/mbe.2023425

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Research article

RETRACTED ARTICLE: A novel architecture design for artificial intelligence-assisted culture conservation management system

Ziqi Zhou ^{1,2
,
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1.
University of the Arts, Cheongju University, Cheongju 360-764, Korea
2.
Performance Academy, Sichuan University of Media and Communications, Chengdu, Sichuan 610000, China
RETRACTED ARTICLE: Retraction published on 18 September 2024, see MBE 2024, 21(9), 7102.

Received: 02 December 2022 Revised: 17 February 2023 Accepted: 19 February 2023 Published: 22 March 2023

Native culture construction has been a prevalent issue in many countries, and its integration with intelligent technologies seems promising. In this work, we take the Chinese opera as the primary research object and propose a novel architecture design for an artificial intelligence-assisted culture conservation management system. This aims to address simple process flow and monotonous management functions provided by Java Business Process Management (JBPM). This aims to address simple process flow and monotonous management functions. On this basis, the dynamic nature of process design, management, and operation is also explored. We offer process solutions that align with cloud resource management through automated process map generation and dynamic audit management mechanisms. Several software performance testing works are conducted to evaluate the performance of the proposed culture management system. The testing results show that the design of such an artificial intelligence-based management system can work well for multiple scenarios of culture conservation affairs. This design has a robust system architecture for the protection and management platform building of non-heritage local operas, which has specific theoretical significance and practical reference value for promoting the protection and management platform building of non-heritage local operas and promoting the transmission and dissemination of traditional culture profoundly and effectively.
- artificial intelligence,
- culture conservation,
- management system,
- architecture design
Citation: Ziqi Zhou. RETRACTED ARTICLE: A novel architecture design for artificial intelligence-assisted culture conservation management system[J]. Mathematical Biosciences and Engineering, 2023, 20(6): 9693-9711. doi: 10.3934/mbe.2023425

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Abstract

Native culture construction has been a prevalent issue in many countries, and its integration with intelligent technologies seems promising. In this work, we take the Chinese opera as the primary research object and propose a novel architecture design for an artificial intelligence-assisted culture conservation management system. This aims to address simple process flow and monotonous management functions provided by Java Business Process Management (JBPM). This aims to address simple process flow and monotonous management functions. On this basis, the dynamic nature of process design, management, and operation is also explored. We offer process solutions that align with cloud resource management through automated process map generation and dynamic audit management mechanisms. Several software performance testing works are conducted to evaluate the performance of the proposed culture management system. The testing results show that the design of such an artificial intelligence-based management system can work well for multiple scenarios of culture conservation affairs. This design has a robust system architecture for the protection and management platform building of non-heritage local operas, which has specific theoretical significance and practical reference value for promoting the protection and management platform building of non-heritage local operas and promoting the transmission and dissemination of traditional culture profoundly and effectively.

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