Research on Assocoation Information Mining of Space Reconnaissance Equipment System Index

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

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.

Key words: space reconnaissance, association rules, index linkage, data mining, FP-Tree (Frequent Pattern-Tree) algorithm

CLC Number:

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.

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