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Assessment of desertification vulnerability using soft computing methods

  • Salvatore RamponeEmail author
  • Alessio Valente
Original Research
  • 74 Downloads

Abstract

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.

Keywords

Desertification Soft computing Artificial neural networks Genetic programming Central Italy 

Notes

Acknowledgements

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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Copyright information

© Springer-Verlag GmbH Germany, part of Springer Nature 2018

Authors and Affiliations

  1. 1.Department of Law, Economics, Management and Quantitative Methods (DEMM)Università del SannioBeneventoItaly
  2. 2.Department of Science and Technology (DST)Università del SannioBeneventoItaly

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