Machine learning for predicting the outcome of terminal ballistics events

Machine learning for predicting the outcome of terminal ballistics events

Machine learning (ML) is well suited for the prediction of high-complexity, high-dimensional problems such as those encountered in terminal ballistics. We evaluate the performance of four popular ML-based regression models, extreme gradient boosting (XGBoost), artificial neural network (ANN), suppor...

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Bibliographic Details
Main Authors: Shannon Ryan, Neeraj Mohan Sushma, Arun Kumar AV, Julian Berk, Tahrima Hashem, Santu Rana, Svetha Venkatesh
Format: Article
Language:English
Published: KeAi Communications Co., Ltd. 2024-01-01
Series:Defence Technology
Subjects:
Machine learning
Artificial intelligence
Physics-informed machine learning
Terminal ballistics
Armour
Online Access:http://www.sciencedirect.com/science/article/pii/S2214914723001940

Internet

http://www.sciencedirect.com/science/article/pii/S2214914723001940

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