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ArticleDevelopment of a quick credibility scoring decision support system using fuzzy TOPSIS

Yusuf Tansel İç2009

Article2009

Development of a quick credibility scoring decision support system using fuzzy TOPSIS

Yusuf Tansel İç · Mustafa Yurdakul

87 citations·0/0 files stored·Expert Systems with Applications

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Multi-Criteria Decision Making Decision Support System Applications Financial Distress and Bankruptcy Prediction

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References

2000Extensions of the TOPSIS for group decision-making under fuzzy environment 1977ZETATM analysis A new model to identify bankruptcy risk of corporations 1997Credit risk measurement: Developments over the last 20 years 2002Evaluating the best main battle tank using fuzzy decision theory with linguistic criteria evaluation 2007Using neural network ensembles for bankruptcy prediction and credit scoring 2000Multi-factor performance measure model with an application to Fortune 500 companies 2003A Fuzzy TOPSIS Method for Robot Selection 2005Building credit scoring models using genetic programming

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2011The LTOPSIS: An alternative to TOPSIS decision-making approach for linguistic variables 2011A mathematical programming approach to multi-attribute decision making with interval-valued intuitionistic fuzzy assessment information 2012Development of a decision support system for robot selection 2013Fuzzy Performance Evaluation with AHP and Topsis Methods: Evidence from Turkish Banking Sector after the Global Financial Crisis 2020Ranking-based MCDM models in financial management applications: analysis and emerging challenges

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Year2009

Typearticle

Published2009-05-21

VenueExpert Systems with Applications

ISSN-L0957-4174

Languageen

Citations87

Files0 public / 0

ShelfMulti-Criteria Decision Making

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doi10.1016/j.eswa.2009.05.038

openalex_workW1970393296

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2016A fuzzy decision support system for credit scoring

2013Balancing accuracy, complexity and interpretability in consumer credit decision making: A C-TOPSIS classification approach

2021A credit scoring model for SMEs using AHP and TOPSIS