Situation Assessment Approach for Air Defense Operation System Based on Force-Sparsed Stacked-Auto Encoding Neural Networks

Authors

Shengming Guo, Joint War College, National Defense University of PLA, Beijing 100091, China;
Xiaoyuan He, Joint War College, National Defense University of PLA, Beijing 100091, China;
Wu Lin, Joint War College, National Defense University of PLA, Beijing 100091, China;
Xiaofeng Hu, Joint War College, National Defense University of PLA, Beijing 100091, China;

Abstract

Abstract: Aiming at the difficulty of feature extraction and related generation mechanism analysis for complex Air Defense System of Systems (ADSOS) using traditional data mining method, a novel situation assessment approach based on Force-Sparsed Stacked-Auto Encoding Neural Networks (FS-SAE) is proposed. Combined with big data and complex networks technology, FS-SAE situation assessment model is built. The emergence relations between the capacity indexes of ADSOS are formalized. And then, the formation mechanism and the contribution rate of capacity indexes are studied and the validity of this approach is validated by the simulation data. The experimental results show that formalized presentation for the emergence process of capacity indexes of ADSOS based on the proposed model not only reflects the complexity characteristics of non-linear and uncertainty in emergence process, but also gives general-defined meaning for indexes structure of ADSOS. It provides a feasible method for the commanders to deeply understand, manage and control the complex operation system.

Recommended Citation

Guo, Shengming; He, Xiaoyuan; Lin, Wu; and Hu, Xiaofeng (2019) "Situation Assessment Approach for Air Defense Operation System Based on Force-Sparsed Stacked-Auto Encoding Neural Networks," Journal of System Simulation: Vol. 30: Iss. 3, Article 2.
DOI: 10.16182/j.issn1004731x.joss.201803002
Available at: https://dc-china-simulation.researchcommons.org/journal/vol30/iss3/2

First Page

772

DOI Link

https://doi.org/10.16182/j.issn1004731x.joss.201803002

Last Page

785

CLC

TP391.9

Recommended Citation

Guo Shengming, He Xiaoyuan, Wu Lin, Hu Xiaofeng. Situation Assessment Approach for Air Defense Operation System Based on Force-Sparsed Stacked-Auto Encoding Neural Networks[J]. Journal of System Simulation, 2018, 30(3): 772-785.

DOI

10.16182/j.issn1004731x.joss.201803002