Abstract
Urban poverty, specially in the metropolitan areas, represent one of the most relevant problems to both developed and developing countries. The objective of the present work is to identify, based on statistical data, territorial zones characterized by the presence of urban poverty, related to property ownership and the availability of residential services. With this problem in mind, there is an attempt to apply a Total Fuzzy and Relative (TFR) approach, based on a fuzzy measure of the degree of association of an individual to the totality of the poor and an approach of Semantic Distance (multicriteria analysis), based on the definition of a “fuzzy distance” as a discriminating multidimensional reference to urban poverty, in the specific case of the City of Bari.
The contribution is the result of joint reflections by the authors, with the following contributions attributed to P. Perchinunno (chapter 2), to F. Rotondo (chapters 1 and 4) and to C. M. Torre. (chapter 3).
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Perchinunno, P., Rotondo, F., Torre, C.M. (2008). A Multivariate Fuzzy Analysis for the Regeneration of Urban Poverty Areas. In: Gervasi, O., Murgante, B., Laganà, A., Taniar, D., Mun, Y., Gavrilova, M.L. (eds) Computational Science and Its Applications – ICCSA 2008. ICCSA 2008. Lecture Notes in Computer Science, vol 5072. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-69839-5_11
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DOI: https://doi.org/10.1007/978-3-540-69839-5_11
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