Applied Mathematics and Nonlinear Sciences
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Journal

Applied Mathematics and Nonlinear Sciences


Volume
& Issue

Volume 9, Issue 1


Published
on

May 3, 2024


Pages


DOI

Article

Construction of fuzzy mathematical model for judging financial indexes of private enterprises under the perspective of deep learning

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Authors

Min Li Affiliation:
School of Economics and Management, Jiangxi University of Software Professional Technology, Nanchang, Jiangxi, 330000, China.
and Yanshi Tu Affiliation:
China Resources Boya Bio-pharmaceutical Group Co, LTD, Fuzhou, Jiangxi, 344000, China.


Abstract

This paper introduces a novel financial evaluation framework combining deep learning, hierarchical analysis, and fuzzy comprehensive evaluation to form the AHP-fuzzy comprehensive model. This model is designed to refine financial analysis by constructing precise evaluation indexes and determining weight values, specifically tailored for the financial management of private enterprises. Through a case study on Enterprise A, focusing on solvency, operational efficiency, and cash flow, we observed significant trends: a decline in the quick ratio from 0.92 in 2017 to 0.49 in 2021, a decrease in the accounts payable turnover ratio from 2.58 in 2017 to 2.01 in 2020, and a concerning downward trend in the cash to current liabilities ratio, culminating in −11.30% in 2020. These findings validate the effectiveness of the AHP-fuzzy comprehensive evaluation model in providing nuanced financial assessments for private enterprises.


Keywords

Deep learning, Hierarchical analysis, Fuzzy comprehensive evaluation, Financial evaluation, 97M50


Citation

Li, M. & Tu, Y. (2024). Construction of fuzzy mathematical model for judging financial indexes of private enterprises under the perspective of deep learning. Applied Mathematics and Nonlinear Sciences, 9(1). https://doi.org/10.2478/amns-2024-0922

Published by: Engineering Journals

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