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Blockchained supply chain management based on IoT tracking and machine learning

When it comes to running and managing modern supply chains, 6G Internet of things (IoT) is of utmost importance. To provide IoT with security and automation, blockchain and machine learning are two upper-layer technology that can help. First, we propose to utilize blockchain in modern supply chains...

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Detalles Bibliográficos
Autores principales: Dong, Zhongping, Liang, Wei, Liang, Yan, Gao, Weibo, Lu, Yi
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Springer International Publishing 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9798956/
https://www.ncbi.nlm.nih.gov/pubmed/36597502
http://dx.doi.org/10.1186/s13638-022-02209-0
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author Dong, Zhongping
Liang, Wei
Liang, Yan
Gao, Weibo
Lu, Yi
author_facet Dong, Zhongping
Liang, Wei
Liang, Yan
Gao, Weibo
Lu, Yi
author_sort Dong, Zhongping
collection PubMed
description When it comes to running and managing modern supply chains, 6G Internet of things (IoT) is of utmost importance. To provide IoT with security and automation, blockchain and machine learning are two upper-layer technology that can help. First, we propose to utilize blockchain in modern supply chains to ensure efficient collaboration between all parties. Second, we adopt multi-head attention (MHA)-based gated recurrent unit (GRU) to do inbound logistics task prediction. Finally, numerical results justify that multi-head attention-based GRU model has better fitting efficiency and prediction accuracy than its counterparts.
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spelling pubmed-97989562022-12-30 Blockchained supply chain management based on IoT tracking and machine learning Dong, Zhongping Liang, Wei Liang, Yan Gao, Weibo Lu, Yi EURASIP J Wirel Commun Netw Research When it comes to running and managing modern supply chains, 6G Internet of things (IoT) is of utmost importance. To provide IoT with security and automation, blockchain and machine learning are two upper-layer technology that can help. First, we propose to utilize blockchain in modern supply chains to ensure efficient collaboration between all parties. Second, we adopt multi-head attention (MHA)-based gated recurrent unit (GRU) to do inbound logistics task prediction. Finally, numerical results justify that multi-head attention-based GRU model has better fitting efficiency and prediction accuracy than its counterparts. Springer International Publishing 2022-12-29 2022 /pmc/articles/PMC9798956/ /pubmed/36597502 http://dx.doi.org/10.1186/s13638-022-02209-0 Text en © The Author(s) 2022 https://creativecommons.org/licenses/by/4.0/Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) .
spellingShingle Research
Dong, Zhongping
Liang, Wei
Liang, Yan
Gao, Weibo
Lu, Yi
Blockchained supply chain management based on IoT tracking and machine learning
title Blockchained supply chain management based on IoT tracking and machine learning
title_full Blockchained supply chain management based on IoT tracking and machine learning
title_fullStr Blockchained supply chain management based on IoT tracking and machine learning
title_full_unstemmed Blockchained supply chain management based on IoT tracking and machine learning
title_short Blockchained supply chain management based on IoT tracking and machine learning
title_sort blockchained supply chain management based on iot tracking and machine learning
topic Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9798956/
https://www.ncbi.nlm.nih.gov/pubmed/36597502
http://dx.doi.org/10.1186/s13638-022-02209-0
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