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- W4297042759 abstract "Interactive art design (IAD) is an organic integration of art and technology. From the perspective of the development of AI machines from ancient times to the present, it has gone through the stages of command interface, graphical interface, and multimedia interface. The development of interactive art has been around for some years. As an art form, it not only brings optimization and enjoyment to people’s quality of life but also meets the needs of human-computer interaction, improves the efficiency of art design, and realizes human-human interaction. The purpose is to bring different feelings and experiences to the works and people’s psychology. In particular, the application of AI in IAD has not only brought great changes to designers. It also derives the interaction of behavioral limbs, which brings a greater experience and interaction to the audience, thereby creating a better interactive effect. Therefore, this paper completes the following work: (1) the research progress of AI in IAD at home and abroad is introduced. (2) The combination of AI and IAD is proposed, and the basic principle of RBF neural network and intelligent optimization algorithm are introduced, and the evaluation index of IAD is constructed. (3) Using the constructed dataset to test two intelligent optimization algorithms, the results show that the PSO-RBF model is more excellent in evaluating the quality of IAD. The trained model is used for experiments, and the output of the model is compared with the expert evaluation results, and the error is very small. Comparing the quality indicators of IAD before and after the integration of AI, the results show that AI has an excellent improvement effect on IAD." @default.
- W4297042759 created "2022-09-26" @default.
- W4297042759 creator A5031449768 @default.
- W4297042759 date "2022-09-25" @default.
- W4297042759 modified "2023-10-14" @default.
- W4297042759 title "Artificial Intelligence-Based Interactive Art Design under Neural Network Vision Valve" @default.
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- W4297042759 doi "https://doi.org/10.1155/2022/3628955" @default.
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