Long and short-term memory neural network multicomponent gas quantification correction algorithm based on sparrow search algorithm

Mingxue Bi; Bingjie Hu; Handong Yu; Xufeng Wang

doi:10.1117/12.3025425

28 February 2024 Long and short-term memory neural network multicomponent gas quantification correction algorithm based on sparrow search algorithm

Mingxue Bi, Bingjie Hu, Handong Yu, Xufeng Wang

Author Affiliations +

Proceedings Volume 13071, International Conference on Mechatronic Engineering and Artificial Intelligence (MEAI 2023); 130712W (2024) https://doi.org/10.1117/12.3025425
Event: International Conference on Mechatronic Engineering and Artificial Intelligence (MEAI 2023), 2023, Shenyang, China

Abstract

This study explores the application of long and short-term memory neural network based on sparrow search algorithm in gas monitoring technology. The SSA-LSTM model is proposed for quantitative monitoring of multi-component gases, and its effectiveness and superiority are verified by utilizing the new algorithm and through experiments, and effective data support is provided for timely warning in the military industry.

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

Citation Download Citation

Mingxue Bi, Bingjie Hu, Handong Yu, and Xufeng Wang "Long and short-term memory neural network multicomponent gas quantification correction algorithm based on sparrow search algorithm", Proc. SPIE 13071, International Conference on Mechatronic Engineering and Artificial Intelligence (MEAI 2023), 130712W (28 February 2024); https://doi.org/10.1117/12.3025425

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