{"title":"Combination of the Data Envelopment Analysis and the Discriminant Analysis for Evaluating Bankrupt Business in a Fuzzy Environment","authors":"N. Torabi, R. Tavakkoli-Moghaddam, A. Siadat","doi":"10.1080/16168658.2022.2117514","DOIUrl":null,"url":null,"abstract":"ABSTRACT This paper presents a combination of the data envelopment analysis (DEA) and discriminant analysis (DA) to evaluate the bankrupt business in a fuzzy environment. The DEA is a non-parametric method that can be used for various assessments. The DA is a statistical method that can predict an appropriate group for new observations. The combination of DEA and DA methods creates a powerful method that includes the advantages of both methods. According to the special features of this method (e.g. high resolution and assessment accuracy), it can be used for a bankruptcy assessment of organisations. In normal conditions, accurate measurement of data is very difficult, which is why considering the uncertainty conditions in models can make them more applied. Using a fuzzy condition in models can help this issue. Finally, the results are illustrated and discussed.","PeriodicalId":37623,"journal":{"name":"Fuzzy Information and Engineering","volume":"45 1","pages":"212 - 227"},"PeriodicalIF":1.3000,"publicationDate":"2022-04-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Fuzzy Information and Engineering","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1080/16168658.2022.2117514","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"MATHEMATICS, APPLIED","Score":null,"Total":0}
引用次数: 1
Abstract
ABSTRACT This paper presents a combination of the data envelopment analysis (DEA) and discriminant analysis (DA) to evaluate the bankrupt business in a fuzzy environment. The DEA is a non-parametric method that can be used for various assessments. The DA is a statistical method that can predict an appropriate group for new observations. The combination of DEA and DA methods creates a powerful method that includes the advantages of both methods. According to the special features of this method (e.g. high resolution and assessment accuracy), it can be used for a bankruptcy assessment of organisations. In normal conditions, accurate measurement of data is very difficult, which is why considering the uncertainty conditions in models can make them more applied. Using a fuzzy condition in models can help this issue. Finally, the results are illustrated and discussed.
期刊介绍:
Fuzzy Information and Engineering—An International Journal wants to provide a unified communication platform for researchers in a wide area of topics from pure and applied mathematics, computer science, engineering, and other related fields. While also accepting fundamental work, the journal focuses on applications. Research papers, short communications, and reviews are welcome. Technical topics within the scope include: (1) Fuzzy Information a. Fuzzy information theory and information systems b. Fuzzy clustering and classification c. Fuzzy information processing d. Hardware and software co-design e. Fuzzy computer f. Fuzzy database and data mining g. Fuzzy image processing and pattern recognition h. Fuzzy information granulation i. Knowledge acquisition and representation in fuzzy information (2) Fuzzy Sets and Systems a. Fuzzy sets b. Fuzzy analysis c. Fuzzy topology and fuzzy mapping d. Fuzzy equation e. Fuzzy programming and optimal f. Fuzzy probability and statistic g. Fuzzy logic and algebra h. General systems i. Fuzzy socioeconomic system j. Fuzzy decision support system k. Fuzzy expert system (3) Soft Computing a. Soft computing theory and foundation b. Nerve cell algorithms c. Genetic algorithms d. Fuzzy approximation algorithms e. Computing with words and Quantum computation (4) Fuzzy Engineering a. Fuzzy control b. Fuzzy system engineering c. Fuzzy knowledge engineering d. Fuzzy management engineering e. Fuzzy design f. Fuzzy industrial engineering g. Fuzzy system modeling (5) Fuzzy Operations Research [...] (6) Artificial Intelligence [...] (7) Others [...]