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Application Analysis of Artificial Intelligence Algorithm in Accounting Field under the Background of Innovation Economy.

Authors :
Chen, Jing
Source :
Mobile Information Systems; 9/5/2022, p1-9, 9p
Publication Year :
2022

Abstract

At present, economic business activities occur to the accounting element confirmation link of the accounting information system (AIS), which still occupies a large amount of manpower and material resources of the enterprise to generate information. This has been restricting the development of modern AIS. Based on this, first, this paper studies the influence of the knowledge economy on accounting innovation and in the innovation economy. The process of confirmation for accounting elements in economic business, under the traditional AIS, is analyzed. Then, the model of the accounting element confirmation, i.e., BPNN, is constructed by combining the backpropagation (BP) neural network (NN) theory with the artificial intelligence (AI) algorithm. Finally, we simulate the confirmation process of accounting elements based on the economic business data of specific online stores. The experimental outcomes illustrate that under the proposed BPNN model, the output value of the accounting entry is also increasing and has been in the interval [0, 0.14] with the continuous increase in the input value of economic business activities. Moreover, the overall simulation error of economic business activity data does not exceed 0.3% in the simulation test of the proposed accounting business data confirmation model based on the BPNN algorithm. The empirical outcomes indicate that the model has high accuracy and reliability. The purpose is to realize the identification of business events by machines and complete the automatic confirmation of accounting elements in the back-end economic business of online stores. This paper provides new ideas for realizing the overall intelligence of the AIS. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
1574017X
Database :
Complementary Index
Journal :
Mobile Information Systems
Publication Type :
Academic Journal
Accession number :
158909523
Full Text :
https://doi.org/10.1155/2022/7970237