Rough Set Approach to Case-Based Reasoning for Operation Risk Analysis under Basel II

2007 ◽  
Author(s):  
Ling Sun ◽  
Jia-yu Chi
Keyword(s):  
Risk Analysis ◽  
Rough Set ◽  
Basel Ii ◽  
Case Based Reasoning ◽  
Operation Risk ◽  
Case Based

scholarly journals Text Case-Based Reasoning Framework for Fault Diagnosis and Predication by Cloud Computing

2018 ◽  
Vol 2018 ◽  
pp. 1-10 ◽  
Author(s):  
Zhiwang Zhong ◽  
Tianhua Xu ◽  
Feng Wang ◽  
Tao Tang
Keyword(s):  
Cloud Computing ◽  
Fault Diagnosis ◽  
Rough Set ◽  
Best Practice ◽  
Discrete Event ◽  
Scale Up ◽  
Case Based Reasoning ◽  
Case Retrieval ◽  
Fault Features ◽  
Case Based

In Discrete Event System, such as railway onboard system, overwhelming volume of textual data is recorded in the form of repair verbatim collected during the fault diagnosis process. Efficient text mining of such maintenance data plays an important role in discovering the best-practice repair knowledge from millions of repair verbatims, which help to conduct accurate fault diagnosis and predication. This paper presents a text case-based reasoning framework by cloud computing, which uses the diagnosis ontology for annotating fault features recorded in the repair verbatim. The extracted fault features are further reduced by rough set theory. Finally, the case retrieval is employed to search the best-practice repair actions for fixing faulty parts. By cloud computing, rough set-based attribute reduction and case retrieval are able to scale up the Big Data records and improve the efficiency of fault diagnosis and predication. The effectiveness of the proposed method is validated through a fault diagnosis of train onboard equipment.

scholarly journals Multi-Attribute Decision Making Based on Attribute Importance Degree and Case-Based Reasoning

2013 ◽  
Vol 13 (Special-Issue) ◽  
pp. 62-74 ◽  
Author(s):  
Zhong Wu ◽  
Ruixia Yan
Keyword(s):  
Decision Making ◽  
Rough Set ◽  
Rough Set Theory ◽  
Importance Measure ◽  
Case Based Reasoning ◽  
Relative Importance ◽  
Attribute Importance ◽  
Decision Making Problem ◽  
Multi Attribute Decision Making ◽  
Case Based

Abstract To tackle a multi-attribute decision making problem, rough set and casebased reasoning are often combined. However, the reduction in a rough set is always complex. In this paper we provide a new relative importance measure about the unitary attributes values by ranking the relative importance of the attributes in the rough set theory. A new rough set model based on ranking the relative importance of the attributes is built and its properties are studied. Then unitary attributes values are utilized to compute the similarity of rules in case-based reasoning, for there might be incompletely match or miss values. A new multiattribute decision making based on case-based reasoning and a rough set based on the ranking relative importance of the attributes is constructed, which obtains rules, avoiding reduction and rule extraction.

Rough set approach to case-based reasoning application

2004 ◽  
Vol 26 (3) ◽  
pp. 369-385 ◽  
Author(s):  
Chun-Che Huang ◽  
Tzu-Liang (Bill) Tseng
Keyword(s):  
Rough Set ◽  
Case Based Reasoning ◽  
Case Based

scholarly journals A combined data mining approach using rough set theory and case-based reasoning in medical datasets

2014 ◽  
Vol 3 (3) ◽  
pp. 285-294 ◽  
Author(s):  
Mohammad Taghi Rezvan ◽  
Ali Zeinal Hamadani ◽  
Babak Saffari ◽  
Ali Shalbafzadeh
Keyword(s):  
Data Mining ◽  
Set Theory ◽  
Rough Set ◽  
Rough Set Theory ◽  
Case Based Reasoning ◽  
Data Mining Approach ◽  
Case Based ◽  
Combined Data

A hybrid approach of rough set and case-based reasoning to remanufacturing process planning

2016 ◽  
Vol 30 (1) ◽  
pp. 19-32 ◽  
Author(s):  
Zhigang Jiang ◽  
Ya Jiang ◽  
Yan Wang ◽  
Hua Zhang ◽  
Huajun Cao ◽  
...  
Keyword(s):  
Process Planning ◽  
Rough Set ◽  
Hybrid Approach ◽  
Case Based Reasoning ◽  
Case Based
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