Title: Risk warning method of computerised accounting information distortion based on deep integration model

Authors: Wenyuan Chen

Addresses: Accounting School, Jiangsu Vocational Institute of Economic and Trade Technology, Nanjing 211168, China

Abstract: In order to improve the early warning accuracy of accounting information distortion risk and reduce the resource occupancy rate in the early warning process, this paper designs a deep integrated model-based computerised accounting information distortion risk early warning method. The distortion risk identification model is constructed to avoid the interference of invalid information and reduce the resource occupancy rate. Then the quantitative index is used to improve its effectiveness and improve the accuracy of the subsequent warning. Then, the deep integration model is used to judge whether there is distortion node in the current computerised accounting information, so as to complete the high precision early warning of distortion risk. Simulation results show that the warning accuracy of this method is always above 0.9, and the resource occupancy rate of the warning process is less than 40%, which proves that this method achieves the design expectation.

Keywords: computerised accounting information; index quantification; distortion risk identification; risk warning; deep integration model.

DOI: 10.1504/IJISE.2023.132263

International Journal of Industrial and Systems Engineering, 2023 Vol.44 No.3, pp.391 - 403

Received: 24 Jun 2021
Accepted: 23 Aug 2021
Published online: 14 Jul 2023 *

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