Prediction of helicopter aircraft material consumption based on partial least squares regression and Markov chain models

Xiaowei Zhang; Wei Zhou; Wentao Dong; Yuanyuan Lin; Wei Cui; Yucai Dong

doi:10.1117/12.3011552

7 December 2023 Prediction of helicopter aircraft material consumption based on partial least squares regression and Markov chain models

Xiaowei Zhang, Wei Zhou, Wentao Dong, Yuanyuan Lin, Wei Cui, Yucai Dong

Author Affiliations +

Proceedings Volume 12941, International Conference on Algorithms, High Performance Computing, and Artificial Intelligence (AHPCAI 2023); 1294126 (2023) https://doi.org/10.1117/12.3011552
Event: Third International Conference on Algorithms, High Performance Computing, and Artificial Intelligence (AHPCAI 203), 2023, Yinchuan, China

Abstract

In order to improve the quality of decision-making on the protection of aerospace materials in land aviation units, the consumption of training aerospace materials in army aviation units is predicted and analyzed. With an army aviation unit training aerospace material consumption as the main research object, the influence factors of helicopter aerospace material consumption are analyzed, partial least squares regression and Markov chain are used to establish a prediction model of helicopter aerospace material consumption, and through the historical data of aerospace material consumption in helicopter training, aerospace material consumption in helicopter training is predicted, and the results show that the partial least squares regression and Markov chain model, which can predict the consumption of helicopter aerial materials more accurately.

(2023) Published by SPIE. Downloading of the abstract is permitted for personal use only.

Citation Download Citation

Xiaowei Zhang, Wei Zhou, Wentao Dong, Yuanyuan Lin, Wei Cui, and Yucai Dong "Prediction of helicopter aircraft material consumption based on partial least squares regression and Markov chain models", Proc. SPIE 12941, International Conference on Algorithms, High Performance Computing, and Artificial Intelligence (AHPCAI 2023), 1294126 (7 December 2023); https://doi.org/10.1117/12.3011552

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