Establishment of Agro-Eco Industrial Clusters: A Romanian Perspective

The Romanian economy feels the need to formalize links between the situational economic forecast and the forecast of technological events in industry and agriculture. The article studies a “dimension” of the organization for classifications of data, structures and economic / agro-eco-industrial even...

Ausführliche Beschreibung

Gespeichert in:
Bibliographische Detailangaben
Veröffentlicht in:European journal of sustainable development 2024-10, Vol.13 (3), p.91
Hauptverfasser: I. GÂF-DEAC, Ioan, Valentina RĂDULESCU, Carmen, MEGA, Loredana, Florin CHIOTAN, Radu
Format: Artikel
Sprache:eng
Online-Zugang:Volltext
Tags: Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
Beschreibung
Zusammenfassung:The Romanian economy feels the need to formalize links between the situational economic forecast and the forecast of technological events in industry and agriculture. The article studies a “dimension” of the organization for classifications of data, structures and economic / agro-eco-industrial events for clustering with the help of “dimensionality”. Meta-prognostic relationships between economics, forecasting and forecasting agents (mathematical elements) are described and the role of metricity, sub-metricity and ultra-metricity in the observation of an automatic ontology for classifications supporting agro-eco-industrial / food clustering is highlighted. The paper proposes the algorithm of the informal classes of supervised / unsupervised data about agro-eco-industrial / food companies in Romania in order to establish classifications that would motivate the formation of clusters in the field. It is concluded that the mathematical apparatus for classification must be developed because based on symbolic mathematical models can be developed computer / computer programs for calculations of ultra-metricity of transformations for linearization’s of similarities between firms, eliminating reminiscences / redundancies, aiming to reduce space / distances between data that represent, in fact, enterprises that can enter agro-eco-industrial / food clusters.     Keywords: agro-eco-industrial clusters, ultra-metricity, clustering, economic forecasting, classification  
ISSN:2239-5938
2239-6101
DOI:10.14207/ejsd.2024.v13n3p91