TY - GEN
T1 - Birnbaum importance measure of network based on C-spectrum under saturated poisson distribution
AU - Du, Y. J.
AU - Si, S. B.
AU - Gao, H. Y.
AU - Cai, Z. Q.
N1 - Publisher Copyright:
© 2017 IEEE.
PY - 2017/7/2
Y1 - 2017/7/2
N2 - Importance measures usually provide numerical indicator to decide which component is more important for network reliability improvement or more critical for network failure. The concept of C-spectrum is a useful tool to implement the importance measures for network, which solely depends on network structure. In this paper, we analyze a network that consists of n components (edges). Under the condition that the distribution of the number of failed edges is given, the properties of traditional Birnbaum importance measure (BIM) are generalized and investigated. First, we derive a formula for BIM based on C-spectrum and establish a sufficient and necessary condition for comparing two edges according to their BIMs. Secondly, under the special case where the number of failed edges follows a saturated Poisson distribution with intensity λ, for enough small λ the BIM ranking is structural ranking, i.e., depending solely on the network structure through the C-spectrum. Finally, an example is presented to explain how we can rank edges according to their BIMs.
AB - Importance measures usually provide numerical indicator to decide which component is more important for network reliability improvement or more critical for network failure. The concept of C-spectrum is a useful tool to implement the importance measures for network, which solely depends on network structure. In this paper, we analyze a network that consists of n components (edges). Under the condition that the distribution of the number of failed edges is given, the properties of traditional Birnbaum importance measure (BIM) are generalized and investigated. First, we derive a formula for BIM based on C-spectrum and establish a sufficient and necessary condition for comparing two edges according to their BIMs. Secondly, under the special case where the number of failed edges follows a saturated Poisson distribution with intensity λ, for enough small λ the BIM ranking is structural ranking, i.e., depending solely on the network structure through the C-spectrum. Finally, an example is presented to explain how we can rank edges according to their BIMs.
KW - Birnbaum importance measure
KW - C-spectrum
KW - network
KW - saturated Poisson distribution
UR - http://www.scopus.com/inward/record.url?scp=85045240795&partnerID=8YFLogxK
U2 - 10.1109/IEEM.2017.8290029
DO - 10.1109/IEEM.2017.8290029
M3 - 会议稿件
AN - SCOPUS:85045240795
T3 - IEEE International Conference on Industrial Engineering and Engineering Management
SP - 934
EP - 938
BT - 2017 IEEE International Conference on Industrial Engineering and Engineering Management, IEEM 2017
PB - IEEE Computer Society
T2 - 2017 IEEE International Conference on Industrial Engineering and Engineering Management, IEEM 2017
Y2 - 10 December 2017 through 13 December 2017
ER -