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Artificial neural network approach to population dynamics of harmful algal blooms in Alfacs Bay (NW Mediterranean): Case studies of Karlodinium and Pseudo-nitzschia

Author

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  • Guallar, Carles
  • Delgado, Maximino
  • Diogène, Jorge
  • Fernández-Tejedor, Margarita
Abstract
The dinoflagellate Karlodinium and the diatom Pseudo-nitzschia are bloom-forming genera frequently present in Alfacs Bay. Both microalgae are associated with toxic events. Therefore, understanding their population dynamics and predict their occurrence in short-term is crucial for an optimal management of toxic events for the local shellfish production and ecosystem managers.

Suggested Citation

  • Guallar, Carles & Delgado, Maximino & Diogène, Jorge & Fernández-Tejedor, Margarita, 2016. "Artificial neural network approach to population dynamics of harmful algal blooms in Alfacs Bay (NW Mediterranean): Case studies of Karlodinium and Pseudo-nitzschia," Ecological Modelling, Elsevier, vol. 338(C), pages 37-50.
    • Handle: RePEc:eee:ecomod:v:338:y:2016:i:c:p:37-50
    DOI: 10.1016/j.ecolmodel.2016.07.009
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    References listed on IDEAS

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    1. Bergmeir, Christoph & Benítez, José M., 2012. "Neural Networks in R Using the Stuttgart Neural Network Simulator: RSNNS," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 46(i07).
    2. Zhang, Guoqiang & Eddy Patuwo, B. & Y. Hu, Michael, 1998. "Forecasting with artificial neural networks:: The state of the art," International Journal of Forecasting, Elsevier, vol. 14(1), pages 35-62, March.
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