2009Computer Science and Information SystemsOpen access

Scoring models: Towards the more realistic approach

Gordana Radojević, Milija Suknović

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Abstract

Financial decision-making is one of the most current issues of modern financial management. Financial decision-making is an area where decision support systems, knowledge-based decision support systems, and intelligent decision support systems are successfully applied. In consequence of the importance and complexity of this problem area a large number of methods of support to financial decisionmaking was developed. This paper presents the most important features of two decision support systems, a classical system and a system based on fuzzy logic. The performances of these two models are compared and the advantages achieved through the introduction of fuzzy concepts into the classical decision support systems are determined.

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Financial decision-making is one of the most current issues of modern financial management. Financial decision-making is an area where decision support systems, knowledge-based decision support systems, and intelligent decision support systems are successfully applied. In consequence of the importance and complexity of this problem area a large number of methods of support to financial decisionmaking was developed. This paper presents the most important features of two decision support systems, a classical system and a system based on fuzzy logic. The performances of these two models are compared and the advantages achieved through the introduction of fuzzy concepts into the classical decision support systems are determined.

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Available abstract

Financial decision-making is one of the most current issues of modern financial management. Financial decision-making is an area where decision support systems, knowledge-based decision support systems, and intelligent decision support systems are successfully applied. In consequence of the importance and complexity of this problem area a large number of methods of support to financial decisionmaking was developed. This paper presents the most important features of two decision support systems, a classical system and a system based on fuzzy logic. The performances of these two models are compared and the advantages achieved through the introduction of fuzzy concepts into the classical decision support systems are determined.

Key concepts: Computer science, Decision support system, Intelligent decision support system, Decision system, Decision engineering, Fuzzy logic, R-CAST, Decision analysis

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