A retrieval-augmented Transformer predicts multi-step port-of-call sequences in global shipping, reporting 72.3% first-destination accuracy and 61.4% three-step accuracy while outperforming CatBoost and LSTM baselines.
2022 International Conference on Electrical, Computer, Communications and Mechatronics Engineering (ICECCME) , pages=
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A Retrieval-Enhanced Transformer for Multi-Step Port-of-Call Sequence Prediction in Global Liner Shipping
A retrieval-augmented Transformer predicts multi-step port-of-call sequences in global shipping, reporting 72.3% first-destination accuracy and 61.4% three-step accuracy while outperforming CatBoost and LSTM baselines.