40 papers take you into the artificial intelligence of "going to day", "Artificial Intelligence and Aerospace" special issue officially launched2022-01-15 18:02:23 22 ℃
As one of the important representatives of the new round of scientific and technological revolution, artificial intelligence is the forefront of today's science and technology field, and its application in the aerospace industry is increasing, and the aerospace industry is constantly changing under the influence of manual intelligence.
To this end, "Aviation Journal" invited Beijing Aerospace
Professor Guo Lei, Professor Liu Tiger and Professor Zhang Weiwei, Northwestern University of Technology, served as the column editor, and invited Chen Zhijie of the Chinese Academy of Engineering as a special issue, with the "Aviation Journal Editor" to edit the group and policies, jointly planning this special issue.
This special issue has a total of 40 papers, including Chen Zhijie and the frontier view of the two academicians of the Xuejun, 14 seriously, and 24 research papers. The latest research progress in the aerial domain management, spacecraft navigation and control, fluid mechanics, and aircraft design.
It is expected to bring it to the majority of aerospace researchers
Thinking and inspiring, rapid development of China Aerospace Science and Technology, and more hopes to promote and solve the theoretical bottlenecks and key common technologies in aerospace applications in aerospace applications.
Please pay attention to this special issue. All papers can be available free of charge through "Aviation Journal".
First, academician view
1. Artificial intelligence enrollment airspace system, enhance the ability of null domain hierarchical governance
Chen Zhijie, Tang Jinhui, Wang Chong, Cheng Ji, Cao Shan, Shao Xin.
Aviation Journal, 2021, 42 (4): 525018.
Link this article: http://hkxb.buaa.edu.cn/10.7527/s1000-6893.2020.25018
2, OODA intelligent communication technology development thinking
Zhu Xijun, Zhao Chang, Liang Zhuo, Tan Qingke
Aviation Journal, 2021, 42 (4): 524332.
Link this article: http://hkxb.buaa.edu.cn/10.7527/s1000-6893.2020.24332
Second, the review article
1. Intelligent communication fluid mechanics prospect
Zhang Weiwei, Yu Jiaqing, Liu Yeng.
Aviation Journal, 2021, 42 (4): 524689.
Link this article: http://hkxb.buaa.edu.cn/10.7527/s1000-6893.2020.24689
2. Summary of research on aerospace autonomous navigation status estimation method
Wang Daji, Hou Bowen, Wang Yueqi, Ge Dongming, Li Mao, Xu Chao, Zhou Haiyin
Aviation Journal 2021, 42 (4): 524310.
Link this article: http://hkxb.buaa.edu.cn/10.7527/s1000-6893.2020.24310
3. Distributed optimization research status and prospects of multi-aircraft
Jiang Xia, Zeng Jialin, Sun Jian, Chen Jie
Aviation Journal 2021, 42 (4): 524551.
Links this article: http://hkxb.buaa.edu.cn/10.7527/s1000-6893.2020.24551
4. A Summary of Application of Artificial Intelligence in Air Guidance and Control
Huang Xu Xing, Li Shuang, Yang Bin, Sun Pan, Liu Xuewen, Liu Xinyan
Aviation Journal 2021, 42 (4): 524201.
Link this article: http://hkxb.buaa.edu.cn/10.7527/s1000-6893.2020.24201
5. Summary of the development of intelligent health management technology in spacecraft control system
Yuan Li, Wang Shuyi
Aviation Journal 2021, (4): 525044.
Link this article: http://hkxb.buaa.edu.cn/10.7527/s1000-6893.2020.25044
6. Summary of the detection research on the target detection of unmanned aerial photography based on deep learning
Jiangbo, Qiwu, Li Yandong, Li Chenglong
Aviation Journal 2021, (4): 524519.
Link this article: http://hkxb.buaa.edu.cn/10.7527/s1000-6893.2020.24519
7. Application and development trend of machine learning in flow control
Ren Feng, Gao Chuanqiang, Tang Hui
Aviation Journal 2021, 42 (4): 524686.
Link this article: http://hkxb.buaa.edu.cn/10.7527/s1000-6893.2020.24686
8. Turbulent data assimilation technology and application
He Chuen, Deng Zhiwen, Liu Yingzheng
Aviation 2021, 42 (4): 524704.
Link this article: http://hkxb.buaa.edu.cn/10.7527/s1000-6893.2020.24704
9. Progress in the identification and application of deep learning flow field based on convolutional neural network
JOURNAL OF HUMANITIES AND SCIENCE AND TECHNOLOGY (NATURAL SCIENCES).
Link this article: http://hkxb.buaa.edu.cn/10.7527/s1000-6893.2020.24736
10. Discussion on Spectrum Intelligent Management Technology in Complex Electromagnetic Environment
Ding Guoxi, Sun Jiayu, Wang Haichao, Jiao Yu Tao
Aviation Journal 2021, 42 (4): 524750.
Link this article: http://hkxb.buaa.edu.cn/10.7527/s1000-6893.2020.24750
11. Aircraft intelligent design vision and key issues
Li Chi, cloth tree Hui, Shang Berlin, Li Yongbo, Tang Zhun, Zhang Weiwei
Aviation Journal 2021, 42 (4): 524752.
Link this article: http://hkxb.buaa.edu.cn/10.7527/s1000-6893.2020.24752
12. Research progress of fluid mechanics deep learning modeling technology
Wang Yi Xing, Han Renkun, Liu Ziyang, Zhang Yang, Chen Gang
Aviation Journal 2021, 42 (4): 524779.
Link this article: http://hkxb.buaa.edu.cn/10.7527/s1000-6893.2020.24779
13. Summary of the development of aviation artificial intelligence concepts and application
Lu Xinlai, Du Ziliang, Xu Wei
Aviation Journal 2021, 42 (4): 525150.
Link this article: http://hkxb.buaa.edu.cn/10.7527/s1000-6893.2021.25150
14. A Summary of Intelligent Flight Technology of Civil Aircraft
Yang Zigang, Zhang Wei, Li Bo, Zeng Rui, Ma Yang
Aviation Journal 2021, 42 (4): 525198.
Link this article: http://hkxb.buaa.edu.cn/10.7527/s1000-6893.2020.25198
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