An empirical analysis of Beijing-Tianjin-Hebei regional economic development level based on unsupervised machine learning

Zhang, Jixin; Shu, Lingjie; Liao, Pengfei

doi:10.1109/ispds54097.2021.00038

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“…AI, including Machine Learning (ML) and Deep Learning (DL), offers advanced and efficient methods for data analysis [3], pattern recognition, economic evaluation [4], and predictive modelling [5,6]. These tools can handle large volumes of complex and heterogeneous data, thus providing valuable insights into economic dynamics at the regional level.…”

Section: Introductionmentioning

confidence: 99%

Regional Economic Development in the AI Era: Methods, Opportunities, and Challenges

Damaševičius

2023

JRE

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<p class="MsoNormal" style="margin-top: 6pt; text-align: justify;"><span lang="EN-US" style="font-family: arial, helvetica, sans-serif;">The dawn of the Artificial Intelligence (AI) era presents a plethora of new possibilities for analyzing regional economic development. The present article provides an in-depth exploration of the methods employed in this field, highlighting the immense opportunities that AI offers while also addressing potential challenges. The role of AI is crucial in complex data handling, enabling efficient analyses of intricate regional economic patterns. This capacity is paramount in shaping economic policies and strategies that are reflective of each region's unique needs and potential. The article firstly explores various AI methods used in economic analysis, including but not limited to machine learning, deep learning, and natural language processing. It delves into the application of these methods in discerning development trends, predicting economic shifts, and identifying strategic economic drivers unique to various regions. Subsequently, the potential of AI to transform regional economic analysis is discussed, encompassing its capability to process large and complex datasets, its power to predict future trends based on past and present data, and its ability to aid in strategic decision-making. However, this new era of AI-driven economic analysis is not without challenges. The latter part of this article thus confronts the issues related to data privacy, ethical use of AI, and the necessity of interdisciplinary skills in AI and economics. This exploration contributes to a broader understanding of how AI is transforming the landscape of regional economic development analysis, illuminating both its present use and future implications. By understanding these dynamics, we can better harness the potential of AI to advance economic prosperity in various regions around the globe.</span></p>

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Section: Introductionmentioning

confidence: 99%

Regional Economic Development in the AI Era: Methods, Opportunities, and Challenges

Damaševičius

2023

JRE

View full text Add to dashboard Cite

show abstract

An empirical analysis of Beijing-Tianjin-Hebei regional economic development level based on unsupervised machine learning

Cited by 1 publication

References 0 publications

Regional Economic Development in the AI Era: Methods, Opportunities, and Challenges

Regional Economic Development in the AI Era: Methods, Opportunities, and Challenges

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