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Deep learning models for straddle carriers: Predictive maintenance
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DOI：10.1016/j.array.2026.100706.png)
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摘要
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• This paper discusses the use of advanced deep learning algorithms for predictive maintenance of straddle carriers. • Some forms of recurrent neural networks and convolutional neural networks are used and compared. • The data preprocessing for sequence-based modeling is described along with hyper parameter tuning and training times. • This is groundwork for improved maintenance procedures driven by data-driven strategies in container terminal operations.
Keyword:
Deep learning
Predictive maintenance
Straddle carriers
Recurrent neural networks
Convolutional neural networks
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期刊
IF:
4.5
论文数:
926
被引数:
1.2K
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