基于人工智能和大数据分析绘制COVID-19 (SARS-CoV-2)大流行对供应链的潜在影响:基于深度学习方法的可持续性框架和程序化研究综述

Sumeet Jhamb
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摘要

这一知识体系侧重于Covid-19通过深度学习方法对全球组织及其供应链或物流机制的人工智能和大数据分析的影响(Queiroz et al., 2020)。当前研究的作者详细阐述了人工智能和大数据分析的定义,以帮助进一步理解和量化新冠肺炎大流行对供应链和小企业的影响(Naude, 2020;Vaishya等人,2020)。在进一步讨论后续影响如何改变公司的技术和数据分析时,我们还指出,组织需要人工智能(AI)、物联网(IoT)、大数据和机器学习等创新技术的支持(Moosavi, Fathollahi-Fard, & Dulebenets, 2022)来对抗和预测新的感染(Queiroz等人,2020)。该研究得出的结论是,COVID-19不仅破坏了科学组织的批判性思维、创新和可持续性能力,而且还恶化了杰出人才未来成功的根本原因(Jamshidi et al., 2020)。
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Mapping the Potential Supply Chain Impressions of the COVID-19 (SARS-CoV-2) Pandemic on Artificial Intelligence and Big Data Analytics: A Sustainability Framework and Programmatic Research Review With Deep Learning Approaches
This body of knowledge focuses on the impacts that Covid-19 has had on Artificial Intelligence and Big Data Analytics of global organizations and their supply chains or logistics mechanisms through deep learning approaches (Queiroz et al., 2020). The authors of the current study detail it out to define Artificial Intelligence and Big Data Analytics to help further understand and quantify the impact that the Covid-19 pandemic has had on broken supply chains and small businesses (Naude, 2020;Vaishya et al., 2020). Going into further discussion on how the after-effects changed technologies and data analytics for companies, we also point out that organizations require the support of innovation technologies like Artificial Intelligence (AI), Internet of Things (IoT), Big Data and Machine Learning (Moosavi, Fathollahi-Fard, & Dulebenets, 2022) to fight and anticipate against new infections (Queiroz, et al., 2020). The study concludes that COVID-19 has not only devastated the critical thinking, innovation, and sustainability capabilities of scientific organizations but has also deteriorated the in-root causes of future successes of brilliant and extraordinary minds (Jamshidi et al., 2020).
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