Compared with previous studies on artificial neural network, this paper expounds the artificial neural network theory, and gives information transfer function and mathematical models of BP neural network. This paper has selected 100 financial crisis companies and 100 non-financial companies as samples crisis, which are in line with the definition of the financial crisis. They has established the enterprise financial crisis model by using BP neural network algorithm, also made a sample test, and the accuracy rate is up to 80%.
목차
Abstract 1. Introduction 2. Artificial Neural Network Theory 2.1 Artificial Neural Network Structure and Learning Ways 2.2. BP Neural Network Information Transfer Function 2.3. BP Neural Network Mathematical Model 3. Financial Early Warning Indicators Selection 4. Financial Crisis Early Warning Model Construction and Simulation 4.1. Financial Crisis Early Warning Model Construction 4.2. Financial Crisis Early Warning Model Simulation 5. Conclusion References
키워드
BP Neural NetworkFinancial CrisisFinancial Crisis Early Warning Model
저자
Yang Xiaobin [ Finance and economics College, Jiangxi University of Technology, Nanchang, Jiangxi, China ]
보안공학연구지원센터(IJUNESST) [Science & Engineering Research Support Center, Republic of Korea(IJUNESST)]
설립연도
2006
분야
공학>컴퓨터학
소개
1. 보안공학에 대한 각종 조사 및 연구
2. 보안공학에 대한 응용기술 연구 및 발표
3. 보안공학에 관한 각종 학술 발표회 및 전시회 개최
4. 보안공학 기술의 상호 협조 및 정보교환
5. 보안공학에 관한 표준화 사업 및 규격의 제정
6. 보안공학에 관한 산학연 협동의 증진
7. 국제적 학술 교류 및 기술 협력
8. 보안공학에 관한 논문지 발간
9. 기타 본 회 목적 달성에 필요한 사업
간행물
간행물명
International Journal of u- and e- Service, Science and Technology
간기
격월간
pISSN
2005-4246
수록기간
2008~2016
십진분류
KDC 505DDC 605
이 권호 내 다른 논문 / International Journal of u- and e- Service, Science and Technology Vol.9 No.9