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International Journal of Biometeorology

, Volume 49, Issue 5, pp 310–316 | Cite as

Artificial neural networks as a useful tool to predict the risk level of Betula pollen in the air

  • M. Castellano-MéndezEmail author
  • M. J. Aira
  • I. Iglesias
  • V. Jato
  • W. González-Manteiga
Original Article

Abstract

An increasing percentage of the European population suffers from allergies to pollen. The study of the evolution of air pollen concentration supplies prior knowledge of the levels of pollen in the air, which can be useful for the prevention and treatment of allergic symptoms, and the management of medical resources. The symptoms of Betula pollinosis can be associated with certain levels of pollen in the air. The aim of this study was to predict the risk of the concentration of pollen exceeding a given level, using previous pollen and meteorological information, by applying neural network techniques. Neural networks are a widespread statistical tool useful for the study of problems associated with complex or poorly understood phenomena. The binary response variable associated with each level requires a careful selection of the neural network and the error function associated with the learning algorithm used during the training phase. The performance of the neural network with the validation set showed that the risk of the pollen level exceeding a certain threshold can be successfully forecasted using artificial neural networks. This prediction tool may be implemented to create an automatic system that forecasts the risk of suffering allergic symptoms.

Keywords

Aerobiology Allergenic risk Binary data Betula pollen Error function Neural networks Pollen level Probability function 

Notes

Acknowledgements

This study was partially funded by the Xunta de Galicia’s Environment Department (PGDIT00MAM38301PR). D.W. González-Manteiga’s work was funded by BFM2002-03213 (European FEDER support included) from the Spanish Ministry of Science and Technology, and by PGIDIT03PXIC20702PN Dirección Xeral de I+D Xunta de Galicia.

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Copyright information

© ISB 2005

Authors and Affiliations

  • M. Castellano-Méndez
    • 1
    Email author
  • M. J. Aira
    • 2
  • I. Iglesias
    • 3
  • V. Jato
    • 3
  • W. González-Manteiga
    • 1
  1. 1.Department of Statistics and Operation ResearchUniversidade de Santiago de CompostelaSantiago de Compostela A CoruñaSpain
  2. 2.Department of Vegetal BiologyUniversidade de Santiago de CompostelaSantiago de Compostela A CoruñaSpain
  3. 3.Departament of Vegetal Biology and Soil SciencesUniversity of VigoSpain

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