An Attention Mechanism Oriented Hybrid CNN-RNN Deep Learning Architecture of Container Terminal Liner Handling Conditions Prediction

The booming computational thinking and deep learning make it possible to construct agile, efficient, and robust deep learning-driven decision-making support engine for the operation of container terminal handling systems (CTHSs). Within the conceptual framework of computational logistics, an attenti...

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Detalles Bibliográficos
Autores principales: Li, Bin, He, Yuqing
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Hindawi 2021
Materias:
Research Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8285194/
https://www.ncbi.nlm.nih.gov/pubmed/34306052
http://dx.doi.org/10.1155/2021/3846078

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8285194/
https://www.ncbi.nlm.nih.gov/pubmed/34306052
http://dx.doi.org/10.1155/2021/3846078

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