An Early-Warning Model of Dam Safety Based on Rough Set Theory and Support Vector Machine

2006 ◽  
Author(s):  
Huai-zhi Su ◽  
Zhi-ping Wen ◽  
Chong-shi Gu
Keyword(s):  
Support Vector Machine ◽  
Set Theory ◽  
Rough Set ◽  
Early Warning ◽  
Rough Set Theory ◽  
Support Vector ◽  
Dam Safety ◽  
Early Warning Model ◽  
Warning Model

Research on Warning Model about Drug Shortage in Hospital Based on RS-SVM

2012 ◽  
Vol 424-425 ◽  
pp. 56-60
Author(s):  
Deng Feng Wu
Keyword(s):  
Support Vector Machine ◽  
Set Theory ◽  
Rough Set ◽  
Rough Set Theory ◽  
Attribute Reduction ◽  
Decision Table ◽  
Support Vector ◽  
Drug Shortage ◽  
Warning Model ◽  
Paper Address

Based on data from hospital and method of empirical analysis, this paper address problem of drug shortage in hospital and try to use rough set theory to trace reason of causing shortage. After attribute reduction of decision table, the paper build a warning model by method of support vector machine to remind hospital to take measure to solve problem in advanced

PREDICTING FINANCIAL DISTRESS OF CHINESE LISTED COMPANIES USING ROUGH SET THEORY AND SUPPORT VECTOR MACHINE

2011 ◽  
Vol 28 (01) ◽  
pp. 95-109 ◽  
Author(s):  
YU CAO ◽  
GUANGYU WAN ◽  
FUQIANG WANG
Keyword(s):  
Support Vector Machine ◽  
Set Theory ◽  
Rough Set ◽  
Financial Distress ◽  
Rough Set Theory ◽  
Listed Companies ◽  
Support Vector ◽  
Financial Distress Prediction ◽  
Distress Prediction ◽  
Chinese Listed Companies

Effectively predicting corporate financial distress is an important and challenging issue for companies. The research aims at predicting financial distress using the integrated model of rough set theory (RST) and support vector machine (SVM), in order to find a better early warning method and enhance the prediction accuracy. After several comparative experiments with the dataset of Chinese listed companies, rough set theory is proved to be an effective approach for reducing redundant information. Our results indicate that the SVM performs better than the BPNN when they are used for corporate financial distress prediction.

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