Component Importance Measure Computation Method Based Fuzzy Integral with Its Application
In view of the negative impact of component importance measures based on system reliability theory and centrality measures based on complex networks theory, there is an attempt to provide improved centrality measures (ICMs) construction method with fuzzy integral for measuring the importance of comp...
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| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
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Wiley
2017-01-01
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| Series: | Discrete Dynamics in Nature and Society |
| Online Access: | http://dx.doi.org/10.1155/2017/7842596 |
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| _version_ | 1832566126526070784 |
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| author | Shuai Lin Yanhui Wang Limin Jia Yang Li |
| author_facet | Shuai Lin Yanhui Wang Limin Jia Yang Li |
| author_sort | Shuai Lin |
| collection | DOAJ |
| description | In view of the negative impact of component importance measures based on system reliability theory and centrality measures based on complex networks theory, there is an attempt to provide improved centrality measures (ICMs) construction method with fuzzy integral for measuring the importance of components in electromechanical systems in this paper. ICMs are the meaningful extension of centrality measures and component importance measures, which consider influences on function and topology between components to increase importance measures usefulness. Our work makes two important contributions. First, we propose a novel integration method of component importance measures to define ICMs based on Choquet integral. Second, a meaningful fuzzy integral is first brought into the construction comprehensive measure by fusion multi-ICMs and then identification of important components which could give consideration to the function of components and topological structure of the whole system. In addition, the construction method of ICMs and comprehensive measure by integration multi-CIMs based on fuzzy integral are illustrated with a holistic topological network of bogie system that consists of 35 components. |
| format | Article |
| id | doaj-art-507471ed4547476ba77a9b301a9a6cfd |
| institution | Kabale University |
| issn | 1026-0226 1607-887X |
| language | English |
| publishDate | 2017-01-01 |
| publisher | Wiley |
| record_format | Article |
| series | Discrete Dynamics in Nature and Society |
| spelling | doaj-art-507471ed4547476ba77a9b301a9a6cfd2025-02-03T01:04:57ZengWileyDiscrete Dynamics in Nature and Society1026-02261607-887X2017-01-01201710.1155/2017/78425967842596Component Importance Measure Computation Method Based Fuzzy Integral with Its ApplicationShuai Lin0Yanhui Wang1Limin Jia2Yang Li3State Key Laboratory of Rail Traffic Control and Safety, Beijing Jiaotong University, Beijing 100044, ChinaState Key Laboratory of Rail Traffic Control and Safety, Beijing Jiaotong University, Beijing 100044, ChinaState Key Laboratory of Rail Traffic Control and Safety, Beijing Jiaotong University, Beijing 100044, ChinaState Key Laboratory of Rail Traffic Control and Safety, Beijing Jiaotong University, Beijing 100044, ChinaIn view of the negative impact of component importance measures based on system reliability theory and centrality measures based on complex networks theory, there is an attempt to provide improved centrality measures (ICMs) construction method with fuzzy integral for measuring the importance of components in electromechanical systems in this paper. ICMs are the meaningful extension of centrality measures and component importance measures, which consider influences on function and topology between components to increase importance measures usefulness. Our work makes two important contributions. First, we propose a novel integration method of component importance measures to define ICMs based on Choquet integral. Second, a meaningful fuzzy integral is first brought into the construction comprehensive measure by fusion multi-ICMs and then identification of important components which could give consideration to the function of components and topological structure of the whole system. In addition, the construction method of ICMs and comprehensive measure by integration multi-CIMs based on fuzzy integral are illustrated with a holistic topological network of bogie system that consists of 35 components.http://dx.doi.org/10.1155/2017/7842596 |
| spellingShingle | Shuai Lin Yanhui Wang Limin Jia Yang Li Component Importance Measure Computation Method Based Fuzzy Integral with Its Application Discrete Dynamics in Nature and Society |
| title | Component Importance Measure Computation Method Based Fuzzy Integral with Its Application |
| title_full | Component Importance Measure Computation Method Based Fuzzy Integral with Its Application |
| title_fullStr | Component Importance Measure Computation Method Based Fuzzy Integral with Its Application |
| title_full_unstemmed | Component Importance Measure Computation Method Based Fuzzy Integral with Its Application |
| title_short | Component Importance Measure Computation Method Based Fuzzy Integral with Its Application |
| title_sort | component importance measure computation method based fuzzy integral with its application |
| url | http://dx.doi.org/10.1155/2017/7842596 |
| work_keys_str_mv | AT shuailin componentimportancemeasurecomputationmethodbasedfuzzyintegralwithitsapplication AT yanhuiwang componentimportancemeasurecomputationmethodbasedfuzzyintegralwithitsapplication AT liminjia componentimportancemeasurecomputationmethodbasedfuzzyintegralwithitsapplication AT yangli componentimportancemeasurecomputationmethodbasedfuzzyintegralwithitsapplication |