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- W4367459405 abstract "Intelligent identification is the main method of financial statement identification, and in the process of enterprise financial statement identification, it is easy to have the problem of large report volume, reduce the accuracy of report identification, and even lose report data. This paper proposes a support vector machine method to identify report recognition and comprehensively shorten the report recognition time. Unusual declarations and financial audits are then identified. Finally, the support vector machine method summarizes the recognition results and outputs the final report recognition. MATLAB shows that the support vector machine method can accurately identify financial statements, with an error rate of less than 10% and a recognition accuracy greater than 90%, which is better than the bee colony algorithm. Therefore, the support vector machine method can meet the requirements of financial statement identification and is suitable for financial statement management." @default.
- W4367459405 created "2023-05-01" @default.
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- W4367459405 date "2023-01-01" @default.
- W4367459405 modified "2023-09-26" @default.
- W4367459405 title "An Enterprise Financial Statement Identification Method Based on Support Vector Machine" @default.
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- W4367459405 doi "https://doi.org/10.1007/978-3-031-31860-3_17" @default.
- W4367459405 hasPublicationYear "2023" @default.
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