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Soft Computing
Erschienen in: Soft Computing 13/2017

11.05.2017 | Focus

Fuzzy transforms prediction in spatial analysis and its application to demographic balance data

verfasst von: Ferdinando Di Martino, Salvatore Sessa

Erschienen in: Soft Computing | Ausgabe 13/2017

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Abstract

We present a new prediction algorithm based on fuzzy transforms for forecasting problems in spatial analysis. Our algorithm allows to predict the spatial distribution of assigned parameters of the problem under exam. Here, we test our method by exploring the demographical balance data measured every month in the period 01/01/2003–31/10/2014 in the municipalities of “Cilento and Vallo di Diano” National Park located in the district of Salerno (Italy). We use this method for predicting the value of the parameters “birthrate” and “deathrate” in November 2014. We apply this process in all the municipalities in the area of study; moreover, we present a fuzzification process for establishing the thematic map of the errors calculated between the real data and the predicted data. The thematic maps are constructed in a GIS environment.
Vorheriger Artikel Pattern matching: overview, benchmark and comparison with F-transform general matching algorithm
Nächster Artikel An extension of F-transforms to more general data: potential applications

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Metadaten
Titel
Fuzzy transforms prediction in spatial analysis and its application to demographic balance data
verfasst von
Ferdinando Di Martino
Salvatore Sessa
Publikationsdatum
11.05.2017
Verlag
Springer Berlin Heidelberg
Erschienen in
Soft Computing / Ausgabe 13/2017
Print ISSN: 1432-7643
Elektronische ISSN: 1433-7479
DOI
https://doi.org/10.1007/s00500-017-2621-8

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