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Title: Rule engine and neural network: reproduction and analysis of traditional festival celebration elements in animation

Authors: Guiming Tian

Addresses: School of Visual Arts, Hunan Mass Media Vocational and Technical College, Changsha 410000, China

Abstract: In this work, a framework based on the combination of generative adversarial network (GAN) and Drools rule engine, Drools-GAN, is suggested to increase the quality of reproduction and generating of traditional festival celebration elements in animation. Combining a generative adversarial network with a rule engine guarantees that the produced images not only meet particular festival aspects and rule criteria but also of great quality. We confirm the advantages of the Drools-GAN framework in terms of image quality, rule compliance, and synergy of its modules by means of a sequence of studies comprising comparison and ablation experiments. The testing results reveal that the framework can guarantee that the produced results fit the preset themes of holiday celebrations and efficiently increase the quality of image generating. The framework shows the possibility for application in animation production and offers a fresh solution for the mix of rule-based image generating.

Keywords: generative adversarial network; GAN; Drools rule engine; festive elements; image generation; animation creation.

DOI: 10.1504/IJICT.2025.145700

International Journal of Information and Communication Technology, 2025 Vol.26 No.7, pp.48 - 62

Received: 10 Feb 2025
Accepted: 19 Feb 2025
Published online: 15 Apr 2025 *