Por favor, use este identificador para citar o enlazar este ítem:https://uvadoc.uva.es/handle/10324/75572
Título
Cultural heritage reuse applying fuzzy expert knowledge and machine learning: Venice’s fortresses case study
Año del Documento
2025
Editorial
Taylor & Francis
Descripción
Producción Científica
Documento Fuente
Camatti, Nicola; di Tollo, Giacomo; Gastaldi, Francesco, & Camerin, F. (2025). Cultural heritage reuse applying fuzzy expert knowledge and machine learning: Venice’s fortresses case study. Regional Studies, Regional Science, 12(1), 225–251
Resumen
This paper presents a comparative analysis of two quantitative models for evaluating the reuse of cultural heritage, using fortified sites in a monofunctional city dedicated to cultural tourism, such as Venice, as a case study. The models explore three distinct reuse scenarios, assessing the appropriateness of each through a combination of fuzzy expert systems (FESs) and self-organising maps (SOMs). An FES acts as an expert-driven approach that formalises problem-solving based on external knowledge, while SOMs provide a data-driven perspective, autonomously processing and aggregating data without relying on external input or predefined assumptions. This innovative methodology facilitates the identification of new functional uses for cultural heritage by leveraging data sources related to the intrinsic structural characteristics of the assets, their territorial context and insights from external experts, alongside pre-established reuse scenarios that guide the analysis. In territories where public policies are fragmented and lack integration, this research provides a critical contribution by addressing the unbalanced distribution of functions across territories. The insights generated from this study offer practical guidance for stakeholders involved in managing cultural heritage, supporting enhanced institutional frameworks that can significantly boost the local economic complexity. This analysis showcases the potential of combining FESs and SOMs as a methodological advancement in the field of cultural heritage research. By illustrating how these tools can be applied together to address broader research challenges, the study contributes to the development of new procedures that can be adapted for use in similar contexts.
Materias Unesco
3329 Planificación Urbana
Palabras Clave
Fuzzy logic
FES
SOM artificial neural network
Machine learning
Urban governance
Cultural heritage reuse
Fortresses
Venice
Revisión por pares
SI
Version del Editor
Propietario de los Derechos
© 2025 The Author(s)
Idioma
eng
Tipo de versión
info:eu-repo/semantics/publishedVersion
Derechos
openAccess
Aparece en las colecciones
Ficheros en el ítem
Tamaño:
1.586Mb
Formato:
Adobe PDF
