Using Machine Learning for Identifying the Intrinsic Economic Specializations of Localities
Using Machine Learning for Identifying the Intrinsic Economic Specializations of Localities
Oliviu Matei, Laura Andreica, Ioan Alin Danci, Anca Avram, Faragău Tudor
Abstract. Identifying the intrinsic economic specialization of localities is a key step in the design of evidence-based regional development and smart specialization strategies. This paper proposes a machine learning approach that combines administrative, economic and socio-demographic indicators in order to discover the latent economic profile of each locality. Supervised and unsupervised techniques are compared, allowing both the classification of localities according to predefined typologies and the detection of emerging specialization patterns. The resulting models provide a data-driven foundation for policy-makers to align regional support measures with the actual potential of each territory.
Keywords: machine learning; regional development; smart specialization; localities; economic profiling
📋 Cite this publication
Oliviu Matei, Laura Andreica, Ioan Alin Danci, Anca Avram, Faragău Tudor, "Using Machine Learning for Identifying the Intrinsic Economic Specializations of Localities", Proc. 19th SOCO Int. Conf. on Soft Computing Models in Industrial and Environmental Applications, Springer, 2024, 2023.
Reference: Proc. 19th SOCO Int. Conf. on Soft Computing Models in Industrial and Environmental Applications, Springer, 2024.
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