Gexiang Zhang

Submitted: 25 October 2026 You are already at the latest version Predicting the unobserved rear half of an acceleration time-history curve can make automotive safety evaluation more efficient. This study compares two deep-learning models, LSTM+CNN and TCN+GAN, for reconstructing post-impact acceleration signals from their observed front halves.

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Open AccessArticle by 1,*, 1,*, 2, 1, 1 and 1 1 School of Mathematics and Computer Science, Wuhan Polytechnic University, Wuhan 430040, China 2 School of Information Science and Technology, Chengdu University of Technology, Chengdu 610059, China * Authors to whom correspondence should be addressed. Appl. Sci.