SELECTION OF MULTIPLE COMBINATION STRATEGIES FOR RISK ASSESSMENT

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Please use this identifier to cite or link to this item: https://irlib.pccu.edu.tw/handle/987654321/29119

Title:	SELECTION OF MULTIPLE COMBINATION STRATEGIES FOR RISK ASSESSMENT
Authors:	Lin, Sin-Jin Wang, Chang-Sheng Hsu, Ming-Fu
Contributors:	化材系
Keywords:	manifold learning hybrid mechanism decision support multiple criteria decision making risk assessment
Date:	2014-11-05
Issue Date:	2015-01-19 14:24:59 (UTC+8)
Abstract:	The effectiveness of precisely predicting whether a corporation will fall into a decline stage is an emerging topic in financial decision making. Faulty decision making by managers can cause a higher possibility of financial failure. Thus, this study introduces a model that incorporates manifold learning and hybrid mechanisms to yield appropriate financial support for users. We generate the hybrid mechanisms through multiple combination strategies. However, it is unknown what kinds of combination strategy can achieve optimal performance. This task can be solved systematically by using an MCDM algorithm. The results indicate that the "classification+classification" combination strategy attains an outstanding performance.
Relation:	CYBERNETICS AND SYSTEMS Volume: 45 Issue: 8 Pages: 622-634
Appears in Collections:	[Department of Chemical & Materials Engineering] journal articles

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