RT info:eu-repo/semantics/article
T1 Cultural heritage reuse applying fuzzy expert knowledge and machine learning: Venice’s fortresses case study
A1 Camatti, Nicola
A1 di Tollo, Giacomo
A1 Gastaldi, Francesco
A1 Camerin, Federico
K1 Fuzzy logic
K1 FES
K1 SOM artificial neural network
K1 Machine learning
K1 Urban governance
K1 Cultural heritage reuse
K1 Fortresses
K1 Venice
K1 3329 Planificación Urbana
AB 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.
PB Taylor & Francis
YR 2025
FD 2025
LK https://uvadoc.uva.es/handle/10324/75572
UL https://uvadoc.uva.es/handle/10324/75572
LA eng
NO 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
NO Producción Científica
DS UVaDOC
RD 16-abr-2025