Table of Contents Author Guidelines Submit a Manuscript
Discrete Dynamics in Nature and Society
Volume 2017, Article ID 7842596, 18 pages
https://doi.org/10.1155/2017/7842596
Research Article

Component Importance Measure Computation Method Based Fuzzy Integral with Its Application

Shuai Lin,1,2 Yanhui Wang,1,3 Limin Jia,1,3 and Yang Li1,2

1State Key Laboratory of Rail Traffic Control and Safety, Beijing Jiaotong University, Beijing 100044, China
2School of Traffic and Transportation, Beijing Jiaotong University, Beijing 100044, China
3Beijing Research Center of Urban Traffic Information Sensing and Service Technologies, Beijing Jiaotong University, Beijing 100044, China

Correspondence should be addressed to Shuai Lin; moc.liamg@umg6102iauhsnil

Received 13 February 2017; Accepted 22 June 2017; Published 17 August 2017

Academic Editor: Manuel De la Sen

Copyright © 2017 Shuai Lin et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Linked References

  1. W. E. Vesely, F. F. Goldberg, N. H. Roberts, and D. F. Haasl, Fault tree handbook. No. NUREG-0492, Nuclear Regulatory Commission, Washington, DC, USA, 1981.
  2. X. Zhu and W. Kuo, “Importance measures in reliability and mathematical programming,” Annals of Operations Research, vol. 212, pp. 241–267, 2014. View at Publisher · View at Google Scholar · View at MathSciNet · View at Scopus
  3. L. W. Birnbaum, “On the importance of different elements in a multi-element system,” Multivariate Analysis, vol. 2, 1969. View at Google Scholar
  4. J. B. Fussell, “How to hand-calculate system reliability and safety characteristics,” IEEE Transactions on Reliability, vol. 3, pp. 169–174, 1975. View at Google Scholar
  5. E. A. Elsayed, Reliability engineering, Addison Wesley Longman, 1996.
  6. J. E. Ramirez-Marquez and W. C. David, “Composite importance measures for multi-state systems with multi-state components,” Reliability, IEEE Transactions on, vol. 54, no. 3, pp. 517–529, 2005. View at Google Scholar
  7. A.-L. Barabsi and R. Albert, “Emergence of scaling in random networks,” Science, vol. 286, no. 5439, pp. 509–512, 1999. View at Publisher · View at Google Scholar · View at MathSciNet
  8. S. H. Strogatz, “Exploring complex networks,” Nature, vol. 410, no. 6825, pp. 268–276, 2001. View at Publisher · View at Google Scholar · View at Scopus
  9. D. Wei, X. Deng, X. Zhang, Y. Deng, and S. Mahadevan, “Identifying influential nodes in weighted networks based on evidence theory,” Physica A: Statistical Mechanics and Its Applications, vol. 392, no. 10, pp. 2564–2575, 2013. View at Publisher · View at Google Scholar · View at Scopus
  10. D. J. Brass and E. B. Marlene, “Centrality and power in organizations,” Networks and Organizations: Structure, Form, and Action, vol. 191, p. 215, 1992. View at Google Scholar
  11. L. C. Freeman, “A set of measures of centrality based on betweenness,” Sociometry, vol. 40, no. 1, pp. 35–41, 1977. View at Publisher · View at Google Scholar
  12. P. Bonacich and L. Paulette, “Eigenvector Centrality and Structural Zeroes and Ones: When Is a Neighbor Not a Neighbor?” Social Networks, vol. 43, pp. 86–90, 2015. View at Google Scholar
  13. B. Dan, L. Li, X. Zhang, F. Guo, and J. Zhou, “Network-integrated manufacturing system,” International Journal of Production Research, vol. 43, no. 12, pp. 2631–2647, 2005. View at Publisher · View at Google Scholar · View at Scopus
  14. Y. Li, X. Chu, D. Chu, and Q. Liu, “An integrated module partition approach for complex products and systems based on weighted complex networks,” International Journal of Production Research, vol. 52, no. 15, pp. 4608–4622, 2014. View at Publisher · View at Google Scholar · View at Scopus
  15. H.-Q. Jiang, J.-M. Gao, F.-M. Chen, and Z.-Y. Gao, “Vulnerability analysis to distributed and complex electromechanical system based on network property,” Computer Integrated Manufacturing Systems, vol. 15, no. 4, pp. 791–796, 2009. View at Google Scholar · View at Scopus
  16. D. G. Xu, Y. Q. Gui, and P. L. Zhao, “Research on reliability of the multi-effect alumina evaporation system based on networks cascading failure model,” in Proceedings of the Control Conference (CCC, 2013 32nd Chinese), pp. 8363–8368, IEEE, 2013.
  17. G. Zong, C. Zhang, and W. Liu, “Study on complexities in relational network of component maintenance for high-speed train in network perspective,” China Railway Science, vol. 34, no. 3, pp. 105–108, 2013. View at Publisher · View at Google Scholar · View at Scopus
  18. T. Gwo-Hshiung, G. H. Tzeng, and J.-J. Huang, Multiple Attribute Decision Making: Methods and Applications, CRC Press, 2011. View at MathSciNet
  19. G. Büyüközkan and S. Güleryüz, “Multi Criteria Group Decision Making Approach for Smart Phone Selection Using Intuitionistic Fuzzy TOPSIS,” International Journal of Computational Intelligence Systems, vol. 9, no. 4, pp. 709–725, 2016. View at Publisher · View at Google Scholar · View at Scopus
  20. D. Joshi and S. Kumar, “Interval-valued intuitionistic hesitant fuzzy Choquet integral based TOPSIS method for multi-criteria group decision making,” European Journal of Operational Research, vol. 248, no. 1, pp. 183–191, 2016. View at Publisher · View at Google Scholar · View at MathSciNet
  21. M. A. Sharaf and H. A. Helmy, “A classification model for inventory management of spare parts,” in Proceedings of the International conference on production, industrial engineering, vol. 7, 2001.
  22. X. Liu and S. An, “Failure propagation analysis of aircraft engine systems based on complex network,” Procedia Engineering, vol. 80, pp. 506–521, 2014. View at Publisher · View at Google Scholar
  23. F. Jin, L. Pei, H. Chen, and L. Zhou, “Interval-valued intuitionistic fuzzy continuous weighted entropy and its application to multi-criteria fuzzy group decision making,” Knowledge-Based Systems, vol. 59, pp. 132–141, 2014. View at Publisher · View at Google Scholar · View at Scopus
  24. K. Govindan, S. Rajendran, J. Sarkis J, and Murugesan., “Multi criteria decision making approaches for green supplier evaluation and selection: a literature review,” Journal of Cleaner Production, vol. 98, pp. 66–83, 2015. View at Google Scholar
  25. E. Zio and L. R. Golea, “Analyzing the topological, electrical and reliability characteristics of a power transmission system for identifying its critical elements,” Reliability Engineering and System Safety, vol. 101, pp. 67–74, 2012. View at Publisher · View at Google Scholar · View at Scopus
  26. Y. Du, C. Gao, Y. Hu, S. Mahadevan, and Y. Deng, “A new method of identifying influential nodes in complex networks based on TOPSIS,” Physica A: Statistical Mechanics and its Applications, vol. 399, pp. 57–69, 2014. View at Publisher · View at Google Scholar · View at Scopus
  27. F. Papadopoulos, C. Psomas, and D. Krioukov, “Replaying the geometric growth of complex networks and application to the as internet,” ACM SIGMETRICS Performance Evaluation Review, vol. 40, no. 3, pp. 104–106, 2012. View at Google Scholar
  28. C. Gan, X. Yang, W. Liu, Q. Zhu, J. Jin, and L. He, “Propagation of computer virus both across the Internet and external computers: a complex-network approach,” Communications in Nonlinear Science and Numerical Simulation, vol. 19, no. 8, pp. 2785–2792, 2014. View at Publisher · View at Google Scholar · View at MathSciNet · View at Scopus
  29. O. Sporns, “Network attributes for segregation and integration in the human brain,” Current Opinion in Neurobiology, vol. 23, no. 2, pp. 162–171, 2013. View at Publisher · View at Google Scholar · View at Scopus
  30. D. R. Carter, L. A. DeChurch, M. T. Braun, and N. S. Contractor, “Social network approaches to leadership: An integrative conceptual review,” Journal of Applied Psychology, vol. 100, no. 3, pp. 597–622, 2015. View at Publisher · View at Google Scholar · View at Scopus
  31. U. Brandes, S. P. Borgatti, and L. C. Freeman, “Maintaining the duality of closeness and betweenness centrality,” Social Networks, vol. 44, pp. 153–159, 2016. View at Publisher · View at Google Scholar · View at Scopus
  32. S. Uddin, H. Liaquat, and W. T. Rolf, “New direction in degree centrality measure: Towards a time-variant approach,” International Journal of Information Technology & Decision Making, vol. 13, no. 4, pp. 865–878, 2014. View at Google Scholar
  33. J. Gao, G. Li, and Z. Gao, “Fault propagation analysis for complex system based on small-world network model,” in Proceedings of the 54th Annual Reliability and Maintainability Symposium, RAMS 2008, IEEE, January 2008. View at Publisher · View at Google Scholar · View at Scopus
  34. E. M. Daly and M. Haahr, “Social network analysis for information flow in disconnected delay-tolerant MANETs,” IEEE Transactions on Mobile Computing, vol. 8, no. 5, pp. 606–621, 2009. View at Publisher · View at Google Scholar · View at Scopus
  35. Y. Wang, L. Bi, S. Lin, M. Li, and H. Shi, “A complex network-based importance measure for mechatronics systems,” Physica A: Statistical Mechanics and its Applications, vol. 466, pp. 180–198, 2017. View at Publisher · View at Google Scholar
  36. M. Sugeno, Theory of fuzzy integrals and its applications [Ph.D. thesis], Tokyo Institute of Technology, Tokyo, Japan, 1974.
  37. M. Sugeno, “Fuzzy measures and fuzzy integrals: a survey,” in Fuzzy Automata and Decision Processes, Gupta, Saridis, and Gaines, Eds., vol. 89, p. 102, 1977. View at Google Scholar
  38. J. J. Liou, Y.-C. Chuang, and G.-H. Tzeng, “A fuzzy integral-based model for supplier evaluation and improvement,” Information Sciences, vol. 266, pp. 199–217, 2014. View at Publisher · View at Google Scholar · View at MathSciNet
  39. L. Zhang, D.-Q. Zhou, P. Zhou, and Q.-T. Chen, “Modelling policy decision of sustainable energy strategies for Nanjing city: a fuzzy integral approach,” Renewable Energy, vol. 62, pp. 197–203, 2014. View at Publisher · View at Google Scholar · View at Scopus
  40. J. Zhai, H. Xu, and Y. Li, “Fusion of extreme learning machine with fuzzy integral,” International Journal of Uncertainty, Fuzziness and Knowledge-Based Systems, vol. 21, supplement 2, no. December 2013, pp. 23–34, 2013. View at Publisher · View at Google Scholar · View at MathSciNet
  41. M. F. Anderson, D. T. Anderson, and D. J. Wescott, “Estimation of adult skeletal age-at-death using the sugeno fuzzy integral,” American Journal of Physical Anthropology, vol. 142, no. 1, pp. 30–41, 2010. View at Publisher · View at Google Scholar · View at Scopus
  42. E. E. Karsak and M. Dursun, “An integrated fuzzy MCDM approach for supplier evaluation and selection,” Computers and Industrial Engineering, vol. 82, pp. 82–93, 2015. View at Publisher · View at Google Scholar · View at Scopus
  43. T. Murofushi and M. Sugeno, “An interpretation of fuzzy measures and the Choquet integral as an integral with respect to a fuzzy measure,” Fuzzy Sets and Systems, vol. 29, no. 2, pp. 201–227, 1989. View at Publisher · View at Google Scholar · View at MathSciNet
  44. M. Grabisch, “The application of fuzzy integrals in multicriteria decision making,” European Journal of Operational Research, vol. 89, no. 3, pp. 445–456, 1996. View at Publisher · View at Google Scholar · View at Scopus
  45. J.-L. Marichal and M. Roubens, “Entropy of discrete fuzzy measures,” International Journal of Uncertainty, Fuzziness and Knowledge-Based Systems, vol. 8, no. 6, pp. 625–640, 2000. View at Publisher · View at Google Scholar · View at MathSciNet