Design of early-warning of enterprise crisis based on entropy model and application

Bao Jun Tang; Wan Hua Qiu

Design of early-warning of enterprise crisis based on entropy model and application

Bao Jun Tang^*
, Wan Hua Qiu

^*此作品的通讯作者

Beihang University

科研成果: 期刊稿件 › 文章 › 同行评审

1 引用（Scopus）

摘要

Due to most of current early-warning difficulties of enterprise crisis in feature extraction and degree classification, the paper presents a method based on entropy. Firstly, J-divergence entropy is applied to feature selection and feature extraction. Then the calculating result is classified to judge state of enterprise with the entropy clustering model. Finally, the results show the feasibility and validity of the model using data acquired from annual reports of A-stock market as samples.

源语言	英语
页（从-至）	43-49
页数	7
期刊	Xitong Gongcheng Lilun yu Shijian/System Engineering Theory and Practice
卷	29
期	4
出版状态	已出版 - 4月 2009
已对外发布	是

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title = "Design of early-warning of enterprise crisis based on entropy model and application",

abstract = "Due to most of current early-warning difficulties of enterprise crisis in feature extraction and degree classification, the paper presents a method based on entropy. Firstly, J-divergence entropy is applied to feature selection and feature extraction. Then the calculating result is classified to judge state of enterprise with the entropy clustering model. Finally, the results show the feasibility and validity of the model using data acquired from annual reports of A-stock market as samples.",

keywords = "Crisis early-warning, Entropy clustering, Feature extraction",

author = "Tang, \{Bao Jun\} and Qiu, \{Wan Hua\}",

year = "2009",

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language = "English",

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T1 - Design of early-warning of enterprise crisis based on entropy model and application

AU - Tang, Bao Jun

AU - Qiu, Wan Hua

PY - 2009/4

Y1 - 2009/4

N2 - Due to most of current early-warning difficulties of enterprise crisis in feature extraction and degree classification, the paper presents a method based on entropy. Firstly, J-divergence entropy is applied to feature selection and feature extraction. Then the calculating result is classified to judge state of enterprise with the entropy clustering model. Finally, the results show the feasibility and validity of the model using data acquired from annual reports of A-stock market as samples.

AB - Due to most of current early-warning difficulties of enterprise crisis in feature extraction and degree classification, the paper presents a method based on entropy. Firstly, J-divergence entropy is applied to feature selection and feature extraction. Then the calculating result is classified to judge state of enterprise with the entropy clustering model. Finally, the results show the feasibility and validity of the model using data acquired from annual reports of A-stock market as samples.

KW - Crisis early-warning

KW - Entropy clustering

KW - Feature extraction

UR - https://www.scopus.com/pages/publications/65649110083

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AN - SCOPUS:65649110083

SN - 1000-6788

VL - 29

SP - 43

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JO - Xitong Gongcheng Lilun yu Shijian/System Engineering Theory and Practice

JF - Xitong Gongcheng Lilun yu Shijian/System Engineering Theory and Practice

IS - 4

ER -

Design of early-warning of enterprise crisis based on entropy model and application

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