Virtual Simulation Design Facing Smart Payment Screen on the Background of Artificial Intelligence

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Abstract

In recent years, the rapid development of virtual simulation technology has become a hot topic among thousands of people. Virtual simulation has been used in education, transportation, anti-theft, and other fields, but it has not seen its application in the field of intelligent payment. This study designed an intelligent payment screen based on virtual simulation technology and evaluated the relevant performance. The evaluation results found that compared with the traditional payment screen, the use of smart payment screen for payment had the fastest improvement in security and the slowest improvement in usability, an increase of 4.2%; the youth group believed that the convenience of use of the smart payment screen based on virtual simulation technology has improved the fastest. The elderly group believed that the use of the smart payment screen based on virtual simulation technology had the slowest improvement in ease of use, an increase of 9.4%; the average payment time of each place has decreased, the average payment time of place 4 was the longest, and the average payment time of place 6 was the shortest, and it was concluded that the higher the payment success rate was, the shortest payment time was; in terms of the user's preference for the smart payment screen, it was concluded that 18:00 was the peak period for users to use the smart payment screen; in terms of risk assessment of using smart payment screens, it was concluded that compared with traditional payment screens, operational risk was reduced by 3.88%, credit risk was reduced by 4.67%, liquidity risk was reduced by 5.06%, and settlement risk was reduced by 6.01%. The design of the smart payment screen makes the user's payment more secure, and the payment risk is greatly reduced.

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APA

Li, Y., & Wang, X. (2022). Virtual Simulation Design Facing Smart Payment Screen on the Background of Artificial Intelligence. Applied Bionics and Biomechanics, 2022. https://doi.org/10.1155/2022/5336548

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