Please use this identifier to cite or link to this item: https://hdl.handle.net/10356/178569
Title: Exploring the structure of the digital economy through blockchain technology and mitigating adverse environmental effects with the aid of artificial neural networks
Authors: Cai, Tengwei
Hong, Zexin
Keywords: Engineering
Issue Date: 2024
Source: Cai, 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.2024.1315812
Journal: Frontiers in Environmental Science 
Abstract: The 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.
URI: https://hdl.handle.net/10356/178569
ISSN: 2296-665X
DOI: 10.3389/fenvs.2024.1315812
Schools: School of Mechanical and Aerospace Engineering 
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.
Fulltext Permission: open
Fulltext Availability: With Fulltext
Appears in Collections:MAE Journal Articles

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