TY - GEN
T1 - Satellite Mission Support Efficiency Evaluation Based on Cascade Decomposition and Bayesian Network
AU - Wang, Ruixing
AU - Li, Yuqing
AU - Zhang, Hailong
AU - Liu, Fan
AU - Lei, Mingjia
N1 - Publisher Copyright:
© 2021, ICST Institute for Computer Sciences, Social Informatics and Telecommunications Engineering.
PY - 2021
Y1 - 2021
N2 - Aiming at the complexity of evaluation system construction is high due to the numerous and jumbled nodes of satellite mission support efficiency evaluation system and the difficulty in identifying the system hierarchy and the relationship between nodes, this paper proposes an evaluation method based on Cascade decomposition and Bayesian network. Firstly, establish a satellite mission support efficiency evaluation system based on Cascade decomposition. According to the basic information of satellite health status and environmental risk, the satellite mission is decomposed into multiple dimensions such as task level, attribute level, measure level and input level. Then, a method based on Bayesian network is designed to extract the experience knowledge, which can represent the complex expert experience mathematically. Finally, an example simulation analysis of earth observation mission is carried out, and the results show that this method can effectively and accurately complete the satellite mission support efficiency evaluation, and verify the validity and correctness of this method.
AB - Aiming at the complexity of evaluation system construction is high due to the numerous and jumbled nodes of satellite mission support efficiency evaluation system and the difficulty in identifying the system hierarchy and the relationship between nodes, this paper proposes an evaluation method based on Cascade decomposition and Bayesian network. Firstly, establish a satellite mission support efficiency evaluation system based on Cascade decomposition. According to the basic information of satellite health status and environmental risk, the satellite mission is decomposed into multiple dimensions such as task level, attribute level, measure level and input level. Then, a method based on Bayesian network is designed to extract the experience knowledge, which can represent the complex expert experience mathematically. Finally, an example simulation analysis of earth observation mission is carried out, and the results show that this method can effectively and accurately complete the satellite mission support efficiency evaluation, and verify the validity and correctness of this method.
KW - Bayesian network
KW - Cascade decomposition
KW - Efficiency evaluation
KW - Satellite
UR - https://www.scopus.com/pages/publications/85103291416
U2 - 10.1007/978-3-030-69072-4_5
DO - 10.1007/978-3-030-69072-4_5
M3 - 会议稿件
AN - SCOPUS:85103291416
SN - 9783030690717
T3 - Lecture Notes of the Institute for Computer Sciences, Social-Informatics and Telecommunications Engineering, LNICST
SP - 46
EP - 60
BT - Wireless and Satellite Systems - 11th EAI International Conference, WiSATS 2020, Proceedings
A2 - Wu, Qihui
A2 - Zhao, Kanglian
A2 - Ding, Xiaojin
PB - Springer Science and Business Media Deutschland GmbH
T2 - 11th EAI International Conference on Wireless and Satellite Systems, WiSATS 2020
Y2 - 17 September 2020 through 18 September 2020
ER -