Construction of fuzzy mathematical model for judging financial indexes of private enterprises under the perspective of deep learning-Reference-Cited by-同舟云学术

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

Published:2024-01-01 Issue:1 Volume:9 Page:
ISSN:2444-8656
Container-title:Applied Mathematics and Nonlinear Sciences
language:en
Short-container-title:

Author:

Li Min¹²,Tu Yanshi³

Affiliation:

1. School of Economics and Management , Jiangxi University of Software Professional Technology , Nanchang , Jiangxi , , China .

2. Philippine Christian University Center for International Education , Manila , , Philippines .

3. China Resources Boya Bio-pharmaceutical Group Co, LTD , Fuzhou , Jiangxi , , China .

Abstract

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.

Publisher

Walter de Gruyter GmbH

Link

https://www.sciendo.com/pdf/10.2478/amns-2024-0922

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