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FUZZY ECONOMIC REVIEW

ISSN (print) 1136-0593 ยท ISSN (online) 2445-4192

FUZZY ECONOMIC REVIEW, Volume IV

Business failure prediction using rough sets: a comparison with multivariate analysis techniques

C. Zopounidis, M. Doumpos. Technical University of Crete

R. Slowinski, R. Susmaga. Poznan University of Technology

A.I. Dimitras. University of Crete

Several multivariate analysis techniques have been used in the past for the prediction of business failure. Although some of these methods lead to models with a satisfactory ability to discriminate between healthy and bankrupt firms, they suffer from some limitations, often due to the unrealistic assumption of statistical hypotheses or…
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The performance requirements analysis with fuzzy logic

G. Zollo, L. Iandoli. University of Naples

A. Cannavacciuolo. Fiat Research Center

This paper presents an innovative approach based on fuzzy logic to the Performance Requirements Analysis which is the first step of Target Costing. This analysis provides relevant information to designers on the importance of functions and components of the product. Traditional models are not able to process qualitative information provided…
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Intuitionistic fuzzy interpretation of information messages

K. Atanassov. Bulgarian Academy of Sciences

D. Dimitrov. University of National and World Economy

The information exchange takes a very important role in several areas of the economic theory. The main question about this process is how the information received can be estimated. In the paper we analyze this exchange of information between a set of informed players and an uninformed player by using…
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The use of fuzzy sets in the assessment of the social cost of electricity generation

S. Mirasgedis, G. Mavrotas, D. Diakoulaki. National Technical University of Athens

Environmental impacts of energy are a great source of market distortion since they impose costs on society which are not taken into account in energy decisions. Recently, significant progress is made in the development of methodologies capable of attributing costs to various types of environmental damages. However, the reliability of…
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Neural networks for railway hazard analysis

G. Bellandi. University of Pisa

R. Dulmin. University of San Marino

The ability of neural networks to learn by example instead of simply applying a set of formalised rules represents an innovative factor of great interest in terms of studying railway reliability. The proposed method overcomes the functional limits of traditional techniques of hazard rate analysis by taking into account several…
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