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Journal of Intelligent Computing
 

File Data Processing using Multiple Neural Feedback Models
He Shujing
University of Indonesia Kampus UI Depok Indonesia
Abstract: File management archives are important records formed by enterprises and government departments in business processing and decision-making, which are of great significance for business continuity, decision-making, and risk management. However, due to various factors such as human error, ageing and damage of archives, the accuracy and reliability of document management archives are often challenged. Therefore, how to effectively test and adjust file management archives has become an important research issue. This article studies a method for testing and adjusting file management archives based on multiple neural feedback models. This method utilizes a multi-neural feedback model to test and regulate file management archives, aiming to improve the accuracy and reliability of file management archives and provide new ideas and methods for research and application in related fields.
Keywords: BP Neural Network, Document File, Management, Research File Data Processing using Multiple Neural Feedback Models
DOI:https://doi.org/10.6025/jic/2023/14/3/78-86
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References:

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