Efficient Fault Diagnosis Method of Electric Power Information System based on Rough Set Theory Knowledge Representation System

2021 ◽  
Author(s):  
Jing Guo ◽  
Di Liu ◽  
Desheng Yang ◽  
Yanbin Jiao
Keyword(s):  
Information System ◽  
Fault Diagnosis ◽  
Knowledge Representation ◽  
Electric Power ◽  
Set Theory ◽  
Rough Set ◽  
Rough Set Theory ◽  
Representation System ◽  
Diagnosis Method ◽  
Knowledge Representation System

A Discretization Method of Continuous Attributes Based on Rough Set

2014 ◽  
Vol 556-562 ◽  
pp. 3711-3713
Author(s):  
Xiao Kang Tang ◽  
Xue Zhi Zhang ◽  
Qiong Zou ◽  
You Guo Wei ◽  
Cheng Jun Cao
Keyword(s):  
Set Theory ◽  
Rough Set ◽  
Rough Set Theory ◽  
Conditional Entropy ◽  
Decision Table ◽  
Representation System ◽  
Specific Data ◽  
Discretization Algorithm ◽  
Discretization Technique ◽  
Knowledge Representation System

when the rough set be used to deal with Knowledge representation system, the data in decision table should be expressed in discrete data, if some conditions or decision attribute is continuous value, which should be discrete Before process.Discretization is not specific data processing only by rough set theory , people have conducted extensive research on discretization problem before the rough set theory put forward , and Made a lot of progress ,but the discretization technique is can not be completely in common used in every subject, different areas have their own unique requirements and handling .This paper proposes a discretization algorithm based on regular conditional entropy.

Research on Fault Diagnosis Method Based on CBR and Rough Set Theory

2012 ◽  
Vol 170-173 ◽  
pp. 3644-3648
Author(s):  
Chun Fei Yuan ◽  
Jing Cai ◽  
Yi Ming Xu
Keyword(s):  
Fault Diagnosis ◽  
Set Theory ◽  
Rough Set ◽  
Rough Set Theory ◽  
Weighting Coefficient ◽  
Case Based Reasoning ◽  
Diagnosis Method ◽  
Maintenance Work ◽  
Fault Diagnosis System ◽  
Case Based

Modern fault diagnosis system always is a dynamic, flexible and uncertain complicated system, so many fault diagnosis methods are not effective to determine fault causes. Considering that abundant of fault diagnosis cases have been accumulated in daily maintenance work, a fault diagnosis method based on case-based reasoning (CBR) and rough set theory is proposed. Rough set theory is employed to process reduction on attributes and the weighting coefficient of case description attributes. This method makes full use of the advantage of" let the data speak". At last the method is testified by an example, and the result shows it is feasible and effective.

One Fault Diagnosis Method Based on Fuzzy Equal Relationship and Rough Set Theory

2014 ◽  
Vol 631-632 ◽  
pp. 175-179
Author(s):  
Si Jie Yang ◽  
Jing Hui Li ◽  
Xiao Ni Liu
Keyword(s):  
Fault Diagnosis ◽  
Set Theory ◽  
Rough Set ◽  
Fuzzy Clustering ◽  
Rough Set Theory ◽  
Relationship Matrix ◽  
Reduction Algorithm ◽  
Diagnosis Method

In order to process the abundant information in fuzzy clustering, one fault diagnosis method was proposed based on Rough Set reduction algorithm and Fuzzy equal relationship clustering. Not only the iteration numbers was reduced in the fuzzy equal relationship matrix, but also the clustering numbers was lower. Then the examples were applied to test its validity.

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