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[½»Á÷] ¡¾2010-03-01¡¿IJNS Special Issue (SCI)

CALL FOR PAPERS   -   SPECIAL ISSUE


INTERNATIONAL JOURNAL OF NEURAL SYSTEMS
Founded in 1989
ON

Credit Scoring and Bankruptcy Prediction with Neural Systems
Editor-in-Chief:
Prof. Hojjat Adeli, The Ohio State University, Columbus, Ohio, U.S.A. (Email: Adeli.1@osu.edu)

Guest Editors:

Dr. Hui Li, School of Business Administration, Zhejiang Normal University, Jinhua 321004, Zhejiang Province, PR China, Email: lihuihit@gmail.com; lihui@zjnu.edu.cn

Prof. Melody Y. Kiang, College of Business Administration, California State University, Long Beach, California 90840, U.S.A., Email: mkiang@csulb.edu

Prof. Diego Andina, Head of Group for Automation in Signals and Communications GASC/UPM, Universidad Polit¨¦cnica de Madrid (UPM), Madrid 28040, Spain, Email: andina@gc.ssr.upm.es

    Credit scoring and bankruptcy prediction have long been recognized as key financial risk management tools for both regulators and stakeholders, especially in today¡¯s globalized and competitive business environment. The main impacts of research in these areas are in decision-support and profitability-analysis of the financial institutions. Though statistical models are still the dominating techniques implemented by the financial and banking industries, credit scoring and bankruptcy prediction systems employing neural computing are gaining increasing attentions due to its potential for i effectiveness and accuracy of the results.  The increasing numbers of commercial bank failures have evolved into an economic crisis that has received much attention in recent years.  The economic aftermath of large-scale bank failures is devastating.  It triggers a domino effect that ripples across different sectors of the economy.  It is therefore both desirable and warranted to explore new techniques and to provide early warnings to regulatory agencies.  The application of neural systems to credit scoring and bankruptcy prediction is now facing a new challenge.

    We invite scholars and professionals from a broad range of disciplines to submit their original work on applying neural systems to credit scoring and bankruptcy prediction. Papers may encompass any or all of the following: theoretical analyses, modeling, and empirical studies. Special topics of interest include, but are not limited to, the following: The application and/or extension of the classical neural systems, hybrid neural systems, ensemble neural systems, fuzzy neural systems, wavelet neural systems, support vector machine, and other novel neural systems to the following problem domains: a) Credit scoring, b) Credit risk evaluation, c) Bankruptcy prediction, d) Business failure prediction, e) Financial distress prediction, and f) Financial crisis prediction. Research on credit scoring and bankruptcy prediction based on current real-world data is especially welcomed.  In such a case, the author(s) should provide detailed description of the data including its source. All manuscripts will be peer-reviewed by at least three referees. Please inform the guest editors and the Editor-in-Chief about your intention to submit a manuscript for possible publication in the special issue as soon as possible, and send the following to the Editor-in-Chief and Guest Editors by March 1, 2010:

1) A statement that this manuscript is your ¡°original unpublished work and the manuscript or any variation of it has not been submitted to another publication previously,¡±

2) A pdf or Word file of your paper using the journal template (attached), and

3) The attached Conscientious Reviewer form for each author (except students).

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Editor-in-Chief:
Prof. Hojjat Adeli, The Ohio State University, Columbus, Ohio, U.S.A. (Email: Adeli.1@osu.edu)

Guest Editors:
Dr. Hui Li, School of Business Administration, Zhejiang Normal University, Jinhua 321004, Zhejiang Province, PR China, Email: lihuihit@gmail.com; lihui@zjnu.edu.cn
Prof. Melody Y. Kiang, College of Business Administration, California State University, Long Beach, California 90840, U.S.A., Email: mkiang@csulb.edu
Prof. Diego Andina, Head of Group for Automation in Signals and Communications GASC/UPM, Universidad Polit¨¦cnica de Madrid (UPM), Madrid 28040, Spain, Email: d.andina@upm.es
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