Assessment of desertification vulnerability using soft computing methods
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In this work Artificial Neural Networks and Genetic Programming are applied in order to assess the desertification status, a kind of land degradation, of an area, from meteorological and land use data. The approach has been tested in the Sannio (central Italy) region. Both the used soft computing methods show low error rates, and the Genetic Programming offers the advantage of an explicit representation of the factors that favour or delay the desertification. This methodology allows preventive actions to face the upcoming desertification.
KeywordsDesertification Soft computing Artificial neural networks Genetic programming Central Italy
The authors are grateful to L. Rampone for the careful reading of the paper.
Compliance with ethical standards
Conflict of interest
The authors declare that there is no conflict of interest regarding the publication of this paper.
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