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.
Benefits and limitations of digitalization in managing European Social funded projects
Benefits and limitations of digitalization in managing European Social funded projectsMatei...
Aggregation Strategy for Federated Machine Learning Algorithm
Aggregation Strategy for Federated Machine Learning AlgorithmRudolf Erdei, Daniela Delinschi,...
Using Markov chains for determining the proximity contagion of smart specialization of localities
Using Markov chains for determining the proximity contagion of smart specialization of...
Advancements in Machine Learning Algorithms for Precision Crop Yield Prediction: A Comprehensive Review with focus on European Union
Advancements in Machine Learning Algorithms for Precision Crop Yield Prediction: A Comprehensive...
TPC Net: An Efficient CNN Architecture for Tomato Plant Disease and Pest Classification
TPC Net: An Efficient CNN Architecture for Tomato Plant Disease and Pest ClassificationOvidiu...
Enhancing API Security Testing against BOLA and Authentication Vulnerabilities through an LLM-Enhanced Framework
Enhancing API Security Testing against BOLA and Authentication Vulnerabilities through an...
A new vision of social behavior on genetic algorithm performance
A new vision of social behavior on genetic algorithm performanceAndreea Tatar, Nicolae Fat, Adrian...
A comparative study of different genetic algorithms approaches to capacitated vehicle routing problem for collection of agricultural products
A comparative study of different genetic algorithms approaches to capacitated vehicle routing...
Embedding GIS in crop field bonitation computation
Embedding GIS in crop field bonitation computationBogdan Văduva, Oliviu Matei, Anca Avram, Laura...
A comparative study of machine learning models for plant disease identification
A comparative study of machine learning models for plant disease identificationMăcelaru Mara,...
A Novel CNN Approach for Accurate Tomato Disease Classification
A Novel CNN Approach for Accurate Tomato Disease ClassificationOvidiu Cosma, Laura Cosma Abstract....
Design of a collaborative network for mapping digital skills for Industry 5.0
Design of a collaborative network for mapping digital skills for Industry 5.0Maria Gustavsson,...
0 Comments