Artificial Intelligence in Economics and Managment: An Edited Proceedings on the Fourth International Workshop: AIEM4 Tel-Aviv, Israel, January 8–10, 1996 - Couverture souple

Couverture souple

ISBN 10 : 1461286204 ISBN 13 : 9781461286202

Editeur : Springer, 2011

Synopsis

In the past decades several researchers have developed statistical models for the prediction of corporate bankruptcy, e. g. Altman (1968) and Bilderbeek (1983). A model for predicting corporate bankruptcy aims to describe the relation between bankruptcy and a number of explanatory financial ratios. These ratios can be calculated from the information contained in a company's annual report. The is to obtain a method for timely prediction of bankruptcy, a so- ultimate purpose called "early warning" system. More recently, this subject has attracted the attention of researchers in the area of machine learning, e. g. Shaw and Gentry (1990), Fletcher and Goss (1993), and Tam and Kiang (1992). This research is usually directed at the comparison of machine learning methods, such as induction of classification trees and neural networks, with the "standard" statistical methods of linear discriminant analysis and logistic regression. In earlier research, Feelders et al. (1994) performed a similar comparative analysis. The methods used were linear discriminant analysis, decision trees and neural networks. We used a data set which contained 139 annual reports of Dutch industrial and trading companies. The experiments showed that the estimated prediction error of both the decision tree and neural network were below the estimated error of the linear discriminant. Thus it seems that we can gain by replacing the "traditionally" used linear discriminant by a more flexible classification method to predict corporate bankruptcy. The data set used in these experiments was very small however.

A propos du livre

Présentation de l'éditeur

This is a carefully edited volume on Artificial Intelligence in Management and Economics from the Fourth International Workshop on the subject. The following themes emerge in the book: the need to use multiple methods in any system designed to solve major real-world problems, a continuing interest in comparing the effectiveness of AI solutions with classic analytical techniques, and a growing use of AI techniques to customize products to suit individual consumers. Each of these themes is discussed within the book's major topical headings: AI Techniques, Financial Applications, Business Applications, Economic Applications, and Qualitative and Cognitive Research. The book will be of interest to both researchers and practitioners.

Détails de l'édition

• Éditeur: Springer
• Date d'édition: 2011
• Langue: anglais
• ISBN 10: 1461286204
• ISBN 13: 9781461286202
• Reliure: Broché
• Nombre de pages: 292
• Éditeur: Ein-Dor Phillip
• Coordonnées du fabricant: non disponible
• Personne responsable: CMN Printpool Inh. Mathis Neumann; https://www.also.com/ec/cms5/en_6000/6000/index.jsp; ; Friedrich-Karl-Str. 9; Hamburg; Allemagne