Research on Assocoation Information Mining of Space Reconnaissance Equipment System Index

Authors

Han Chi, Space Engineering University, Beijing 101416, China;
Xiong Wei, Space Engineering University, Beijing 101416, China;

Abstract

Abstract: The system effectiveness and system contribution rate of the Space Reconnaissance Equipment System (SRES) has a large number of mutally associated indicators. How to identify relationships the association, select the key indicators and clarify the assocition between core indicators and system contribution rate are the key of the evaluation of system effectiveness and contribution rate. Through the joint simulation of MATLAB and STK, the underlying index data of SRES is obtained. Based on the Frequent Pattern-Tree (FP-Tree) algorithm, the assocition information is discovered, the redundancy is removed and the type of indicator assocition is determined, and an optimization model is established to determine the contribution of the key indicators by combining Marichal entropy. Simulation experiment results show that the FP-Tree algorithm can be used to mine the assocition and its types between the initial evaluation index system, determine the index contribution and realize the streamlining of the index system.

Recommended Citation

Chi, Han and Wei, Xiong (2021) "Research on Assocoation Information Mining of Space Reconnaissance Equipment System Index," Journal of System Simulation: Vol. 33: Iss. 10, Article 10.
DOI: 10.16182/j.issn1004731x.joss.20-0553
Available at: https://dc-china-simulation.researchcommons.org/journal/vol33/iss10/10

First Page

2372

Revised Date

2020-10-13

DOI Link

https://doi.org/10.16182/j.issn1004731x.joss.20-0553

Last Page

2380

CLC

N945.13;TP391

Recommended Citation

Han Chi, Xiong Wei. Research on Assocoation Information Mining of Space Reconnaissance Equipment System Index[J]. Journal of System Simulation, 2021, 33(10): 2372-2380.

DOI

10.16182/j.issn1004731x.joss.20-0553