Please use this identifier to cite or link to this item: https://hdl.handle.net/10356/178569
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dc.contributor.authorCai, Tengweien_US
dc.contributor.authorHong, Zexinen_US
dc.date.accessioned2024-06-26T04:59:41Z-
dc.date.available2024-06-26T04:59:41Z-
dc.date.issued2024-
dc.identifier.citationCai, T. & Hong, Z. (2024). Exploring the structure of the digital economy through blockchain technology and mitigating adverse environmental effects with the aid of artificial neural networks. Frontiers in Environmental Science, 12, 1315812-. https://dx.doi.org/10.3389/fenvs.2024.1315812en_US
dc.identifier.issn2296-665Xen_US
dc.identifier.urihttps://hdl.handle.net/10356/178569-
dc.description.abstractThe rapid expansion of the digital economy has had a transformative impact on society, presenting both opportunities and challenges. This article aims to examine the structure of the digital economy and its implications, with a specific focus on the adverse environmental effects associated with its rapid growth. To address these challenges, the utilization of artificial neural networks is proposed as a viable solution. ANNs have proven to be effective in analyzing large volumes of data and extracting valuable insights. By integrating blockchain technology and harnessing the power of ANNs, this study seeks to develop management strategies that optimize resource allocation, reduce waste, and promote sustainability within the digital economy. Through comprehensive data analysis, patterns and trends can be identified, providing decision-makers with valuable information to make informed choices that minimize the environmental impact of digitalization. This research significantly contributes to the existing body of knowledge by enhancing our understanding of the digital economy’s structure, particularly in the context of blockchain technology. The ANN in this study estimated the impact of digital economy growth and structure improvement on adverse environmental effects, waste reduction, and environmental sustainability. The predictions showed that increasing digital economy growth led to increased waste reduction and promotion of environmental sustainability, while adverse environmental effects exhibited sinusoidal behavior. Linear regression confirmed the acceptable error of the network’s predictions compared to experimental results. Furthermore, it sheds light on the potential of ANNs to mitigate the adverse environmental effects associated with the digital economy. By emphasizing the importance of sustainable practices and exploring the applications of emerging technologies, this study offers valuable insights for policymakers, researchers, and industry practitioners seeking to navigate the complex landscape of the digital economy while minimizing its environmental consequences.en_US
dc.language.isoenen_US
dc.relation.ispartofFrontiers in Environmental Scienceen_US
dc.rights© 2024 Cai and Hong. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.en_US
dc.subjectEngineeringen_US
dc.titleExploring the structure of the digital economy through blockchain technology and mitigating adverse environmental effects with the aid of artificial neural networksen_US
dc.typeJournal Articleen
dc.contributor.schoolSchool of Mechanical and Aerospace Engineeringen_US
dc.identifier.doi10.3389/fenvs.2024.1315812-
dc.description.versionPublished versionen_US
dc.identifier.scopus2-s2.0-85188532152-
dc.identifier.volume12en_US
dc.identifier.spage1315812en_US
dc.subject.keywordsDigital economyen_US
dc.subject.keywordsBlockchain technologyen_US
item.grantfulltextopen-
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