RETRACTED ARTICLE: Enriching Regional Economic Dynamics through a Knowledge-Driven Spatial Analysis Model: a Deep Learning Approach

Hin Yu Micah Cheung ()
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Hin Yu Micah Cheung: New York University

Journal of the Knowledge Economy, 2024, vol. 15, issue 3, No 84, 12293-12336

Abstract: Abstract Based on spatial interaction theory and relevant economic paradigms, in conjunction with the principles of crafting an evaluation framework, this study meticulously selects socio-economic impact indicators that adeptly characterize the course of regional economic development. As a result, a comprehensive socio-economic impact indicator system is formulated to gauge the dynamics of regional economic progress. The research computes the holistic weightage of these indicators by harnessing the capabilities of deep learning algorithms to streamline the dimensionality of indicator data. By harnessing the power of the independent sub-analysis algorithm, the study constructs a spatial analysis model through data transformation and reclassification, fostering a harmonious interaction between the regional economic development system and the socio-economic factor system. The proposed methodology is applied to assess the economic development of a city, unveiling that the study area’s overall economic trajectory falls within the mid-to-upper echelon. Notably, the region showcases elevated levels of urbanization and regional cultural vibrancy. This innovative approach aligns seamlessly with the spirit of advancing knowledge-based economic insights and regional evolution.

Keywords: Spatial interaction theory; Regional economic development; Deep learning algorithms; Urbanization; Regional cultural vibrancy (search for similar items in EconPapers)
Date: 2024
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DOI: 10.1007/s13132-023-01531-2

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