GreyART Network for Financial Distress Prediction Problem

IF 1 4区工程技术 Q4 MATHEMATICS, INTERDISCIPLINARY APPLICATIONS

Journal of Grey System Pub Date : 2006-06-01 DOI:10.30016/JGS.200606.0006

M. Yeh, Haoxun Yang, Chia-Ting Chang

引用次数: 1

Abstract

This study attempts to use the GreyART network to construct a financial distress prediction model. The inputs applied to the network are the historical data containing 18 different financial ratios of 54 healthy and 22 distressed Taiwan's listed electronic firms. In order to determine the best result the GreyART network can attain, a new performance index is developed. Simulation results show the one using 8 variables to generate only four clusters, 1 for healthy class and 3 for distressed class with corresponding classification hit rates of 94.12% and 93.55% for the training and test phases, respectively.

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财务危机预测问题的GreyART网络

本研究尝试使用GreyART网路建构财务困境预测模型。该网络的输入是包含54家健康和22家不良台湾上市电子公司18种不同财务比率的历史数据。为了确定GreyART网络所能达到的最佳效果，提出了一种新的性能指标。仿真结果表明，使用8个变量只生成4个聚类，其中健康类1个，痛苦类3个，训练和测试阶段的分类命中率分别为94.12%和93.55%。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

Journal of Grey System 数学-数学跨学科应用

CiteScore

2.40

自引率

43.80%

发文量

审稿时长

1.5 months

期刊介绍： The journal is a forum of the highest professional quality for both scientists and practitioners to exchange ideas and publish new discoveries on a vast array of topics and issues in grey system. It aims to bring forth anything from either innovative to known theories or practical applications in grey system. It provides everyone opportunities to present, criticize, and discuss their findings and ideas with others. A number of areas of particular interest (but not limited) are listed as follows: Grey mathematics- Generator of Grey Sequences- Grey Incidence Analysis Models- Grey Clustering Evaluation Models- Grey Prediction Models- Grey Decision Making Models- Grey Programming Models- Grey Input and Output Models- Grey Control- Grey Game- Practical Applications.