Optimization of weights for air combat situation assessment based on NRO

Cheng Hua; Xie Lei; Wang Yong; Wu Bing; Zhang Peng

doi:10.1117/12.3049702

8 November 2024 Optimization of weights for air combat situation assessment based on NRO

Cheng Hua, Xie Lei, Wang Yong, Wu Bing, Zhang Peng

Author Affiliations +

Proceedings Volume 13416, Fourth International Conference on Advanced Algorithms and Neural Networks (AANN 2024); 1341608 (2024) https://doi.org/10.1117/12.3049702
Event: 2024 4th International Conference on Advanced Algorithms and Neural Networks, 2024, Qingdao, China

Abstract

The weights of various factors in air combat situation assessment are determined by experts, which has certain subjectivity and limitations. This manuscript uses heuristic optimization algorithms to optimize the weights. Firstly, the advantage functions of angle, speed, altitude, and distance are established, and the close-range air combat status information is quantified as situational description parameters. Secondly, use the physical heuristic nuclear reaction optimization (NRO) algorithm to optimize the situational function weights, achieving the optimal situational combination. Through a set of air combat situational weight optimization experiment, the results show that NRO is better than the selected comparative optimization algorithms.

(2024) Published by SPIE. Downloading of the abstract is permitted for personal use only.

Citation Download Citation

Cheng Hua, Xie Lei, Wang Yong, Wu Bing, and Zhang Peng "Optimization of weights for air combat situation assessment based on NRO", Proc. SPIE 13416, Fourth International Conference on Advanced Algorithms and Neural Networks (AANN 2024), 1341608 (8 November 2024); https://doi.org/10.1117/12.3049702

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