QAmplifyNet: pushing the boundaries of supply chain backorder prediction using interpretable hybrid quantum-classical neural network

Supply chain management relies on accurate backorder prediction for optimizing inventory control, reducing costs, and enhancing customer satisfaction. Traditional machine-learning models struggle with large-scale datasets and complex relationships. This research introduces a novel methodological fra...

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Detalles Bibliográficos
Autores principales: Jahin, Md Abrar, Shovon, Md Sakib Hossain, Islam, Md. Saiful, Shin, Jungpil, Mridha, M. F., Okuyama, Yuichi
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2023
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10600161/
https://www.ncbi.nlm.nih.gov/pubmed/37880386
http://dx.doi.org/10.1038/s41598-023-45406-7

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10600161/
https://www.ncbi.nlm.nih.gov/pubmed/37880386
http://dx.doi.org/10.1038/s41598-023-45406-7

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