<abstract xmlns="http://www.w3.org/1999/xhtml">

<p>By exploring the application of artificial intelligence technology in visual communication design, the design efficiency and innovation of visual communication can be effectively improved. In order to automatically arrange graphic language in visual communication design, a novel algorithm is proposed in this research, together with a functional model of artificial intelligence technology design. The minimum and maximum values of the number of orchestrated pages are used as the objective orchestration function for calculating the display size of buffer images in visual communication design. In visual communication design, an ant colony method is used to determine where graphics should be displayed best, and ASM semantics is used to describe the graphics language. The proposed algorithm is programmed and runs to achieve the innovation and development of visual communication design style by using the parallel selection mark to describe the graphic language and realize the automatic arrangement. The experimental results show that the visual saturation obtained based on artificial intelligence technology can reach up to 97%, the mean value of user satisfaction is 7.789, and the TGB consideration characteristics are evenly distributed. It can be seen that an innovative visual thinking mode can convey novel design concepts in visual communication design and optimize the visual communication design effect.</p>
</abstract>

By exploring the application of artificial intelligence technology in visual communication design, the design efficiency and innovation of visual communication can be effectively improved. In order to automatically arrange graphic language in visual communication design, a novel algorithm is proposed in this research, together with a functional model of artificial intelligence technology design. The minimum and maximum values of the number of orchestrated pages are used as the objective orchestration function for calculating the display size of buffer images in visual communication design. In visual communication design, an ant colony method is used to determine where graphics should be displayed best, and ASM semantics is used to describe the graphics language. The proposed algorithm is programmed and runs to achieve the innovation and development of visual communication design style by using the parallel selection mark to describe the graphic language and realize the automatic arrangement. The experimental results show that the visual saturation obtained based on artificial intelligence technology can reach up to 97%, the mean value of user satisfaction is 7.789, and the TGB consideration characteristics are evenly distributed. It can be seen that an innovative visual thinking mode can convey novel design concepts in visual communication design and optimize the visual communication design effect.

Exploring the innovation of visual communication design style based on artificial intelligence technology

Changsha University of Science & Technology

Applied Mathematics and Nonlinear Sciences

This work is licensed under the Creative Commons Attribution 4.0 International License.

By exploring the application of artificial intelligence technology in visual communication design, the design efficiency and innovation of visual communication...

Exploring the innovation of visual communication design style based on artificial intelligence technology

Online veröffentlicht: 07. Okt. 2023

Seitenbereich: -

Eingereicht: 21. Nov. 2022

Akzeptiert: 17. Apr. 2023

DOI: https://doi.org/10.2478/amns.2023.2.00507

Schlüsselwörter
Artificial intelligence technology, Automatic scheduling algorithm, Fixed-value method, Ant colony algorithm, Scheduling objective function, ASM semantics

© 2023 Haian Yan et al., published by Sciendo

This work is licensed under the Creative Commons Attribution 4.0 International License.

Exploring the innovation of visual communication design style based on artificial intelligence technology

Online veröffentlicht: 07. Okt. 2023

Seitenbereich: -

Eingereicht: 21. Nov. 2022

Akzeptiert: 17. Apr. 2023

DOI: https://doi.org/10.2478/amns.2023.2.00507

SchlüsselwörterArtificial intelligence technology, Automatic scheduling algorithm, Fixed-value method, Ant colony algorithm, Scheduling objective function, ASM semantics

© 2023 Haian Yan et al., published by Sciendo

This work is licensed under the Creative Commons Attribution 4.0 International License.

Schlüsselwörter
Artificial intelligence technology, Automatic scheduling algorithm, Fixed-value method, Ant colony algorithm, Scheduling objective function, ASM semantics