English  |  正體中文  |  简体中文  |  Items with full text/Total items : 28607/40644
Visitors : 4747990      Online Users : 359
RC Version 4.0 © Powered By DSPACE, MIT. Enhanced by NTU Library IR team.
Scope Adv. Search

Please use this identifier to cite or link to this item: http://ntour.ntou.edu.tw:8080/ir/handle/987654321/45078

Title: An Application of Neural Network on Early Warning System by Rating for the Credit Department of Fishermen Association in Taiwan
Authors: 莊慶達;劉祥熹;吳明峰
Contributors: 國立臺灣海洋大學:海洋事務與資源管理研究所
Date: 2004
Issue Date: 2017-12-28T01:08:43Z
Publisher: the 12 th Biennial Conference of IIFET
Abstract: Abstract:This paper applies the Back-Propagation Network (BPN) to build the financial distress prediction models. Empirical results show that the effect of BPN on crisis management mechanisms towards communities' financial institutions in Taiwan is doing quite fine. In addition, the predictability comparison indicates that the highest accuracy is the Primitive BPN (81.1%) in the surveillance system, followed by the Factory BPN (77.85%) and the Ordered Logit (75.9%). Damages and impacts to the fishing community and industry are always far more serious when financial crises occur in the community's financial institutions. Thus, a more accurate financial warning system for governing these financial institutions is needed more than ever. The artificial neural network (ANN) suggested in this study can provide a bankruptcy predictor of financial distress among credit unions.
URI: http://ntour.ntou.edu.tw:8080/ir/handle/987654321/45078
Appears in Collections:[海洋事務與資源管理研究所] 演講及研討會

Files in This Item:

File Description SizeFormat

All items in NTOUR are protected by copyright, with all rights reserved.


著作權政策宣告: 本網站之內容為國立臺灣海洋大學所收錄之機構典藏,無償提供學術研究與公眾教育等公益性使用,請合理使用本網站之內容,以尊重著作權人之權益。
網站維護: 海大圖資處 圖書系統組
DSpace Software Copyright © 2002-2004  MIT &  Hewlett-Packard  /   Enhanced by   NTU Library IR team Copyright ©   - Feedback