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The "Art-Risk 3.0" research project has developed a new tool to address the challenges faced in maintaining and preserving cultural heritage. This tool aims to evaluate the functional operational age and life cycle of heritage buildings in the Arc de Berà area in Tarragona, Catalonia, Spain, with the goal of promoting preventive conservation through a multidisciplinary approach. The tool considers various factors that contribute to the condition of heritage buildings, including structural stability, material decay, environmental risks, and usage patterns. By employing a fuzzy model, it provides an assessment of the building's condition in historical sites. One of the key features of the Art-Risk tool is its ability to prioritize intervention among different case studies within a specific urban context. It generates three output results: vulnerability, risk, and functionality index. The vulnerability value indicates the level of vulnerability of a building, with lower values suggesting better structural stability and resilience against potential hazards. The risk value signifies the level of risk associated with a building, with lower values indicating a reduced likelihood of damage or deterioration. The functionality index reflects the operational condition and suitability of a building for its intended use, with higher values indicating better functionality and operational performance, by considering these diverse valuations, stakeholders and conservation plan managers can effectively establish priorities for intervention. Buildings with higher vulnerability, risk, or lower functionality index scores are given higher priority for intervention. This approach ensures that limited resources are allocated to the buildings that require immediate attention, maximizing the impact of conservation efforts. Art-Risk3.0 model incorporates 19 input variables, with five variables automatically assigned based on the building's geographic location. Users are required to provide valid geographical coordinates and the remaining 14 associated values to obtain an accurate assessment of the building's condition. [ABSTRACT FROM AUTHOR]

Abstract: In recent years, fuzzy models have been acknowledged as a suitable approach for species distribution modelling due to their transparency and their ability to incorporate the ecological gradient theory. Specifically, the overlapping class boundaries of a fuzzy model are similar to the transitions between different environmental conditions. However, the need for ecological expert knowledge is an important constraint when applying fuzzy species distribution models. Moreover, the consistency of the ecological preferences of some fish species across different rivers has been widely contested. Recent research has shown that data-driven fuzzy models may solve this ‘knowledge acquisition bottleneck’ and this paper is a further contribution. The aim was to analyse the brown trout (Salmo trutta fario L.) habitat preferences based on a data-driven fuzzy modelling technique and to compare the resulting fuzzy models with a commonly applied modelling technique, Random Forests. A heuristic nearest ascent hill-climbing algorithm for fuzzy rule optimisation and Random Forests were applied to analyse the ecological preferences of brown trout in 93 mesohabitats. No significant differences in model performance were observed between the optimal fuzzy model and the Random Forests model and both approaches selected river width, the cover index and flow velocity as the most important variables describing brown trout habitat suitability. Further, the fuzzy model combined ecological relevance with reasonable interpretability, whereas the transparency of the Random Forests model was limited. This paper shows that fuzzy models may be a valid approach for species distribution modelling and that their performance is comparable to that of state-of-the-art modelling techniques like Random Forests. Fuzzy models could therefore be a valuable decision support tool for river managers and enhance communication between stakeholders. [Copyright &y& Elsevier]