Applied Mathematics and Nonlinear Sciences
Journal license

Journal

Applied Mathematics and Nonlinear Sciences


Volume
& Issue

Volume 8, Issue 1


Published
on

June 6, 2023


Pages

2053-2060


DOI

Article

Graphic Design Optimization Method Based on Deep Reinforcement Learning Model

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Authors

Jiwen Zhang Affiliation:
School of Fashion, Henan Institute of Science and Technology, Xinxiang, 453003, China


Abstract

This paper used a new interior graphic modeling research based on CAD and depth enhancement teaching models. A massive database for graphic design has been established. An optimization method is proposed based on intelligent decision making, intelligent monitoring, panoramic vision, professional cooperation and intelligent planning. This system can make many systems of different dimensions share and integrate horizontally. The graphic design of CAD is introduced into 3D CAD. The Boolean method is introduced into the smooth grid instruction to obtain the smooth surface of the target surface. Combining the object of plane decomposition with other geometric shapes by form-fitting instruction achieves object control. Experiments show the effectiveness of the method. The system has good running performance, stability and safety.


Keywords

Computer-aided, Deep reinforcement learning model, Interior graphic design, Rendering processing, Decision model, 92B20


Citation

Zhang, J. (2023). Graphic design optimization method based on deep reinforcement learning model. Applied Mathematics and Nonlinear Sciences, 8(1), 2053–2060. https://doi.org/10.2478/amns.2023.1.00309

Published by: Engineering Journals

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