A CNN Based Cognitive Method to Battlefields Encompassing Situation with Insufficient Samples

Authors

Zhu Feng, 1. The Department of Information Operation and Command Training, National Defense University, Beijing 100091, China;;2. No. 93682 Unit of PLA, Beijing 101300, China;;
Xiaofeng Hu, 1. The Department of Information Operation and Command Training, National Defense University, Beijing 100091, China;;
Xiaoyuan He, 1. The Department of Information Operation and Command Training, National Defense University, Beijing 100091, China;;
Yisi Kong, 1. The Department of Information Operation and Command Training, National Defense University, Beijing 100091, China;;
Yang Lu, 3. No. 91053 Unit of PLA, Beijing 100070, China;;4. Air and Missile Defense College, Air Force Engineering University, Xi'an 710051, China;

Abstract

Abstract: To research the issue of how to grasp the commander's cognitive experience successfully and effectively facing to battlefields sight map, Convolution Neural Network (CNN) as a kind of the typical algorithm in deep learning can provide the key ways. However, CNN needs the enough samples for running. These samples are hardly to achieve for the time being. Aimed at these problems, some exploring researches were carried out. The issues of battlefields encompassing situation cognition met generally in the warfare and lacking enough samples were discussed. On the basis of analyzing the image characteristics of battlefields encompassing situation and the operational principles of CNN, a new method of battlefields encompassing situation cognition based on CNN without enough samples was proposed. In the method, the non-linear fitting function of CNN and the symmetry characteristics of the battlefields encompassing situation images were utilized to catch the commander's experience for cognizing the battlefields encompassing situation at a certain extent. Simulation results validate the effectiveness and the robustness of the proposed method.

Recommended Citation

Feng, Zhu; Hu, Xiaofeng; He, Xiaoyuan; Kong, Yisi; and Lu, Yang (2020) "A CNN Based Cognitive Method to Battlefields Encompassing Situation with Insufficient Samples," Journal of System Simulation: Vol. 29: Iss. 10, Article 9.
DOI: 10.16182/j.issn1004731x.joss.201710009
Available at: https://dc-china-simulation.researchcommons.org/journal/vol29/iss10/9

First Page

2291

DOI Link

https://doi.org/10.16182/j.issn1004731x.joss.201710009

Last Page

2300

CLC

TP183

Recommended Citation

Zhu Feng, Hu Xiaofeng, He Xiaoyuan, Kong Yisi, Yang Lu. A CNN Based Cognitive Method to Battlefields Encompassing Situation with Insufficient Samples[J]. Journal of System Simulation, 2017, 29(10): 2291-2300.

DOI

10.16182/j.issn1004731x.joss.201710009