Abstract
The development of science and technology has constantly changed the air combat battlefield. At present, more and more researches focus on the optimization of air combat pilot Expert System(ES). The ES can be divided into two parts: tactical state decision-making and maneuver behavior decision-making. Although a lot of work had optimized the generation method of maneuver behavior decision-making, the tactical state decision-making still follows the original human rules. Based on a large number of tactical state decision-making sample data, this paper uses data-driven method to build a deep learning network. Experiments showed that this method can learn high-level decision empirical data and replace rule models, and can be applied to pilot’s accurate tactical state decision-making in the future.
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This work was supported by the Special Project of Academician Aiguo Fei’s Workstation, No. 400119Z012.
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Mao, Y., **a, Z., Li, Q., He, J., Fei, A. (2022). Accurate Decision-Making Method for Air Combat Pilots Based on Data-Driven. In: Tan, Y., Shi, Y. (eds) Data Mining and Big Data. DMBD 2022. Communications in Computer and Information Science, vol 1745. Springer, Singapore. https://doi.org/10.1007/978-981-19-8991-9_31
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DOI: https://doi.org/10.1007/978-981-19-8991-9_31
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