JIPS (한국정보처리학회)
Current Result Document : 5 / 6
| 한글제목(Korean Title) |
A Novel Unweighted Combination Method for Business Failure Prediction Using Soft Set |
| 영문제목(English Title) |
A Novel Unweighted Combination Method for Business Failure Prediction Using Soft Set |
| 저자(Author) |
Jinjie Wen
Zhengxu Zhao
Qian Zhong
Wei Xu
Daoli Yang
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| 원문수록처(Citation) |
VOL 15 NO. 06 PP. 1489 ~ 1502 (2019. 12) |
한글내용
(Korean Abstract) |
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영문내용
(English Abstract) |
This work introduces a novel unweighted combination method (UCSS) for business failure perdition (BFP). With considering features of BFP in the age ofbig data, UCSS integrates the quantitative and qualitative analysis by utilizing soft set theory (SS). We adopt the conventional expert system (ES) as the basic qualitative classifier, the logistic regression model (LR) and the support vector machine (SVM) as basic quantitative classifiers. Unlike other traditional combination methods, we employ soft set theory to integrate the results of each basic classifier without weighting. In this way, UCSS inherits the advantages of ES, LR, SVM, and SS. To verify the performance ofUCSS, it is applied to real datasets. We adopt ES, LR, SVM, combination models utilizing the equal weight approach (CMEW), neural network algorithm (CMNN), rough set and D-S evidence theory (CMRD), and the receiver operating characteristic curve (ROC) and SS (CFBSS) as benchmarks. The superior performance ofUCSS has been verified by the empirical experiments.
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| 키워드(Keyword) |
Formal method
Interplanetary Transportation
Net Assessment
Teleoperation System
Trustworthy Evidence
Business Failure Prediction
Combination Method
Different Sample Sizes
Soft Set
uni-int Decision Making Method
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