Paper
16 June 2023 A CatBoost-based data driven method for equipment effectiveness assessment and prediction
Ling Ye, Lingyun Lu, Xin Gao, Chenyu Huang
Author Affiliations +
Proceedings Volume 12702, International Conference on Intelligent Systems, Communications, and Computer Networks (ISCCN 2023); 1270218 (2023) https://doi.org/10.1117/12.2680660
Event: International Conference on Intelligent Systems, Communications, and Computer Networks (ISCCN 2023), 2023, Changsha, China
Abstract
Simulation-based design plays an important role in the study and manufacturing of weapon equipment, in which effectiveness evaluation is one of essential tasks. While a variety of effectiveness evaluation approaches have been proposed, they are becoming incapable with the increase in the complexity of weapon equipment systems. In this case, data driven methods have been explored to address the effectiveness evaluation issue. In this paper, we propose a new CatBoost based data driven method for assessing and predicting the effectiveness of equipment and give a procedure for guiding the use of this method. We illustrate our method with an air defense missile weapon system, which demonstrates the validity of our method compared with state-of-the-art methods.
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Ling Ye, Lingyun Lu, Xin Gao, and Chenyu Huang "A CatBoost-based data driven method for equipment effectiveness assessment and prediction", Proc. SPIE 12702, International Conference on Intelligent Systems, Communications, and Computer Networks (ISCCN 2023), 1270218 (16 June 2023); https://doi.org/10.1117/12.2680660
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KEYWORDS
Data modeling

Machine learning

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