Operational effectiveness index sensitivity analysis method of fighter plane based on machine learning

Jinpeng Bai; Fengxing Pan; Yibo Song; Yaoming Zhou

doi:10.1117/12.2653035

20 October 2022 Operational effectiveness index sensitivity analysis method of fighter plane based on machine learning

Jinpeng Bai, Fengxing Pan, Yibo Song, Yaoming Zhou

Proceedings Volume 12350, 6th International Workshop on Advanced Algorithms and Control Engineering (IWAACE 2022); 123502H (2022) https://doi.org/10.1117/12.2653035
Event: 6th International Workshop on Advanced Algorithms and Control Engineering (IWAACE 2022), 2022, Qingdao, China

Abstract

With the development of technology, the status and role of the air force in the future war are becoming more and more important. As the main component of the air force strength, the importance of the research and development of fighters are becoming more and more prominent. Researches on operational effectiveness evaluation can effectively promote the development of high-performance weapon systems such as fighter. Among these researches, sensitivity analysis of effectiveness index can establish mapping relationships between performance index and the effectiveness index when aircrafts finally participate in a combat, at the early stage of aircraft design, and guide the demonstration of aircraft index, reducing the development cycle and cost. In this paper, a sensitivity analysis method of effectiveness index based on machine learning is proposed, aiming at the performance index of fighter with different granularity. Neural network is used to fit a large number of simulation data, and mine the implicit relationship between the data, then analyze the sensitivity of performance index (i.e., sensitive factor) to the final effectiveness index, so as to guide aircraft design and parameter index trade-off.

Citation Download Citation

Jinpeng Bai, Fengxing Pan, Yibo Song, and Yaoming Zhou "Operational effectiveness index sensitivity analysis method of fighter plane based on machine learning", Proc. SPIE 12350, 6th International Workshop on Advanced Algorithms and Control Engineering (IWAACE 2022), 123502H (20 October 2022); https://doi.org/10.1117/12.2653035

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