loading
Papers Papers/2022 Papers Papers/2022

Research.Publish.Connect.

Paper

Paper Unlock

Authors: Ning Chen and Armando Vieira

Affiliation: Instituto Politecnico do Porto, Portugal

Keyword(s): Bankruptcy prediction, Learning vector quantization, Independent component analysis.

Related Ontology Subjects/Areas/Topics: Artificial Intelligence ; Biomedical Engineering ; Biomedical Signal Processing ; Computational Intelligence ; Data Manipulation ; Evolutionary Computing ; Health Engineering and Technology Applications ; Human-Computer Interaction ; Knowledge Discovery and Information Retrieval ; Knowledge-Based Systems ; Machine Learning ; Methodologies and Methods ; Neural Networks ; Neurocomputing ; Neurotechnology, Electronics and Informatics ; Pattern Recognition ; Physiological Computing Systems ; Sensor Networks ; Signal Processing ; Soft Computing ; Symbolic Systems ; Theory and Methods

Abstract: Bankruptcy prediction is of great importance in financial statement analysis to minimize the risk of decision strategies. It attempts to separate distress companies from healthy ones according to some financial indicators. Since the real data usually contains irrelevant, redundant and correlated variables, it is necessary to reduce the dimensionality before performing the prediction. In this paper, a hybrid bankruptcy prediction algorithm is proposed based on independent component analysis and learning vector quantization. Experiments show the algorithm is effective for high dimensional bankruptcy data and therefore improve the capability of prediction.

CC BY-NC-ND 4.0

Sign In Guest: Register as new SciTePress user now for free.

Sign In SciTePress user: please login.

PDF ImageMy Papers

You are not signed in, therefore limits apply to your IP address 3.142.119.241

In the current month:
Recent papers: 100 available of 100 total
2+ years older papers: 200 available of 200 total

Paper citation in several formats:
Chen, N. and Vieira, A. (2009). BANKRUPTCY PREDICTION BASED ON INDEPENDENT COMPONENT ANALYSIS. In Proceedings of the International Conference on Agents and Artificial Intelligence - ICAART; ISBN 978-989-8111-66-1; ISSN 2184-433X, SciTePress, pages 150-155. DOI: 10.5220/0001536301500155

@conference{icaart09,
author={Ning Chen. and Armando Vieira.},
title={BANKRUPTCY PREDICTION BASED ON INDEPENDENT COMPONENT ANALYSIS},
booktitle={Proceedings of the International Conference on Agents and Artificial Intelligence - ICAART},
year={2009},
pages={150-155},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0001536301500155},
isbn={978-989-8111-66-1},
issn={2184-433X},
}

TY - CONF

JO - Proceedings of the International Conference on Agents and Artificial Intelligence - ICAART
TI - BANKRUPTCY PREDICTION BASED ON INDEPENDENT COMPONENT ANALYSIS
SN - 978-989-8111-66-1
IS - 2184-433X
AU - Chen, N.
AU - Vieira, A.
PY - 2009
SP - 150
EP - 155
DO - 10.5220/0001536301500155
PB - SciTePress

- Science and Technology Publications, Lda.
RESOURCES

Proceedings

Papers

Authors

Ontology

CONTACTS

Science and Technology Publications, Lda
Avenida de S. Francisco Xavier, Lote 7 Cv. C,
2900-616 Setúbal, Portugal.

Phone: +351 265 520 185 (National fixed network call)
Fax: +351 265 520 186
Email: info@scitepress.org

EXTERNAL LINKS

PRIMORIS

INSTICC

SCITEVENTS

CROSSREF

PROCEEDINGS SUBMITTED FOR INDEXATION BY:

dblp

Ei Compendex

SCOPUS

Semantic Scholar

Google Scholar

Microsoft Academic