A Multivariate Fuzzy Analysis for the Regeneration of Urban Poverty Areas
ICCSA '08 Proceeding sof the international conference on Computational Science and Its Applications, Part I
Clustering for the localization of degraded urban areas
ICCSA'12 Proceedings of the 12th international conference on Computational Science and Its Applications - Volume Part II
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The paper show the use of a fuzzy weighting system to identify the correspondence of real estate value with main socio-physical characters of the urban tissue. The descriptor of the relationship with the real estate value is represented by a set of indicators of the urban decay of housing property and the analysis is tested on a real application of a case study. The study gives support to the development of new approach for localizing cadastral values at a more detailed scale, compared to the current scale used in the Italian Cadastre. The utilized statistical approach has been based on the SaTScan application, as a techniques of fuzzy clustering, and on a test of stability based on the comparison of a “fuzzy semantic distance” among the average real estate values of urban quarters, with the expected crisp distance among the same quarters.