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Development of an adaptive business insolvency classifier prototype (AVICENA) using hybrid intelligent algorithms

Confronted by an increasingly competitive environment and chaotic economic conditions, businesses are faced with the need to accept greater risk.Businesses do not become insolvent overnight, rather creditors, investors and the financial community will receive either direct or indirect indications th...

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Main Authors: Ab. Aziz, Azizi, Siraj, Fadzilah, Zakaria, Azizi
Format: Conference or Workshop Item
Language:English
Published: 2002
Subjects:
QA76 Computer software
Online Access:http://repo.uum.edu.my/12329/1/01033085.pdf
http://repo.uum.edu.my/12329/
http://dx.doi.org/10.1109/SCORED.2002.1033085
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spelling my.uum.repo.123292014-10-23T02:08:18Z http://repo.uum.edu.my/12329/ Development of an adaptive business insolvency classifier prototype (AVICENA) using hybrid intelligent algorithms Ab. Aziz, Azizi Siraj, Fadzilah Zakaria, Azizi QA76 Computer software Confronted by an increasingly competitive environment and chaotic economic conditions, businesses are faced with the need to accept greater risk.Businesses do not become insolvent overnight, rather creditors, investors and the financial community will receive either direct or indirect indications that a company is experiencing financial distress.Thus, this paper analyzed the ability of AVICENA to classify business insolvency performance events.Neural networks (multilayer perceptron-backpropagation) serves as a classifier mechanism while a priori algorithms (auto association rules) support the decision made by the neural networks, in which rules are generated.The conventional model for predicting business performance, the Altman-Z scores model, is used for performance comparison. 2002 Conference or Workshop Item PeerReviewed application/pdf en http://repo.uum.edu.my/12329/1/01033085.pdf Ab. Aziz, Azizi and Siraj, Fadzilah and Zakaria, Azizi (2002) Development of an adaptive business insolvency classifier prototype (AVICENA) using hybrid intelligent algorithms. In: Student Conference on Research and Development (SCOReD 2002), 2002. http://dx.doi.org/10.1109/SCORED.2002.1033085 doi:10.1109/SCORED.2002.1033085
institution Universiti Utara Malaysia
building UUM Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Utara Malaysia
content_source UUM Institutionali Repository
url_provider http://repo.uum.edu.my/
language English
topic QA76 Computer software
spellingShingle QA76 Computer software
Ab. Aziz, Azizi
Siraj, Fadzilah
Zakaria, Azizi
Development of an adaptive business insolvency classifier prototype (AVICENA) using hybrid intelligent algorithms
description Confronted by an increasingly competitive environment and chaotic economic conditions, businesses are faced with the need to accept greater risk.Businesses do not become insolvent overnight, rather creditors, investors and the financial community will receive either direct or indirect indications that a company is experiencing financial distress.Thus, this paper analyzed the ability of AVICENA to classify business insolvency performance events.Neural networks (multilayer perceptron-backpropagation) serves as a classifier mechanism while a priori algorithms (auto association rules) support the decision made by the neural networks, in which rules are generated.The conventional model for predicting business performance, the Altman-Z scores model, is used for performance comparison.
format Conference or Workshop Item
author Ab. Aziz, Azizi
Siraj, Fadzilah
Zakaria, Azizi
author_facet Ab. Aziz, Azizi
Siraj, Fadzilah
Zakaria, Azizi
author_sort Ab. Aziz, Azizi
title Development of an adaptive business insolvency classifier prototype (AVICENA) using hybrid intelligent algorithms
title_short Development of an adaptive business insolvency classifier prototype (AVICENA) using hybrid intelligent algorithms
title_full Development of an adaptive business insolvency classifier prototype (AVICENA) using hybrid intelligent algorithms
title_fullStr Development of an adaptive business insolvency classifier prototype (AVICENA) using hybrid intelligent algorithms
title_full_unstemmed Development of an adaptive business insolvency classifier prototype (AVICENA) using hybrid intelligent algorithms
title_sort development of an adaptive business insolvency classifier prototype (avicena) using hybrid intelligent algorithms
publishDate 2002
url http://repo.uum.edu.my/12329/1/01033085.pdf
http://repo.uum.edu.my/12329/
http://dx.doi.org/10.1109/SCORED.2002.1033085
_version_ 1644280884263649280
score 13.145126

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