Knowledge management system National Space Science Center,CAS
| Satellite networks coordination situation assessment method based on convolution neural network | |
| Alternative Title | 20202908937838;基于卷积神经网络的卫星网络协调态势评估方法 |
| Gao, Xiang1,2,3,4; Liu, Heguang1,3; Chen, Zhimin1,2; Yao, Xiujuan1,2; Wang, Chunmei1,2 | |
| Source Publication | Guofang Keji Daxue Xuebao/Journal of National University of Defense Technology
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| 2020 | |
| Volume | 42Issue:3Pages:56-65 |
| DOI | 10.11887/j.cn.202003008 |
| ISSN | 10012486 |
| Language | 中文 |
| Keyword | Convolution - Decision making - Digital storage - Efficiency - Geostationary satellites - Learning algorithms - Machine learning - Orbits Convolution neural network - Evaluation modeling - Geostationary satellite orbits - Measurement methods - Resource acquisition - Resource selection - Situation analysis - Situation assessment |
| Abstract | In order to fully explore the use of massive satellite network data, improve decision-making efficiency, and strengthen the analysis methods of spatial frequency and orbit resource acquisition and storage, especially for the GSO (geostationary satellite orbit) resource selection problem, a satellite network situation assessment strategy based on machine learning algorithm was proposed. By analyzing the characteristics of satellite network coordination factors, the CNN (convolutional neural network) was selected as the target algorithm model, and the training data set and label rules of the algorithm model were established. The data is reduced by the split information gain measurement method and a CNN evaluation model was established. Afterwards, a verification analysis was performed. Results show that the CNN model has a correct rate of 80% or more for the satellite network coordination situation assessment problem, and has high evaluation efficiency. Moreover, with the increase of the amount of data, the evaluation effect of CNN is gradually improved, which indicates the proposed method is an effective evaluation method for coordination situation analysis and resource reserve in satellite networks. © 2020, NUDT Press. All right reserved. |
| Indexed By | EI ; CSCD |
| Citation statistics | |
| Document Type | 期刊论文 |
| Identifier | http://ir.nssc.ac.cn/handle/122/7496 |
| Collection | 中国科学院国家空间科学中心 |
| Affiliation | 1.National Space Science Center, Chinese Academy of Sciences, Beijing; 100190, China; 2.Laboratory of Electronic and Information Technology for Space Systems, Chinese Academy of Sciences, Beijing; 100190, China; 3.Key Laboratory of Microwave Remote Sensing, Chinese Academy of Sciences, Beijing; 100190, China; 4.University of Chinese Academy of Sciences, Beijing; 100049, China |
| Recommended Citation GB/T 7714 | Gao, Xiang,Liu, Heguang,Chen, Zhimin,et al. Satellite networks coordination situation assessment method based on convolution neural network[J]. Guofang Keji Daxue Xuebao/Journal of National University of Defense Technology,2020,42(3):56-65. |
| APA | Gao, Xiang,Liu, Heguang,Chen, Zhimin,Yao, Xiujuan,&Wang, Chunmei.(2020).Satellite networks coordination situation assessment method based on convolution neural network.Guofang Keji Daxue Xuebao/Journal of National University of Defense Technology,42(3),56-65. |
| MLA | Gao, Xiang,et al."Satellite networks coordination situation assessment method based on convolution neural network".Guofang Keji Daxue Xuebao/Journal of National University of Defense Technology 42.3(2020):56-65. |
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