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Mining monitored data for decision-making with a Bayesian network model

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  • Williams, B.J.
  • Cole, B.

Abstract

A Bayesian network model of Anabaena blooms in Grahamstown Dam, near Newcastle, Australia is described. This model meets the criteria of being decision-focused, data driven, transparent, and capable of being used by non-expert modellers.

Suggested Citation

  • Williams, B.J. & Cole, B., 2013. "Mining monitored data for decision-making with a Bayesian network model," Ecological Modelling, Elsevier, vol. 249(C), pages 26-36.
    • Handle: RePEc:eee:ecomod:v:249:y:2013:i:c:p:26-36
    DOI: 10.1016/j.ecolmodel.2012.07.008
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    References listed on IDEAS

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    1. Ticehurst, Jenifer L. & Letcher, Rebecca A. & Rissik, David, 2008. "Integration modelling and decision support: A case study of the Coastal Lake Assessment and Management (CLAM) Tool," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 78(2), pages 435-449.
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    Cited by:

    1. Moe, S. Jannicke & Haande, Sigrid & Couture, Raoul-Marie, 2016. "Climate change, cyanobacteria blooms and ecological status of lakes: A Bayesian network approach," Ecological Modelling, Elsevier, vol. 337(C), pages 330-347.
    2. Mulazzani, Luca & Manrique, Rosa & Malorgio, Giulio, 2017. "The Role of Strategic Behaviour in Ecosystem Service Modelling: Integrating Bayesian Networks With Game Theory," Ecological Economics, Elsevier, vol. 141(C), pages 234-244.
    3. Ülengin, Füsun & Önsel, Şule & Aktas, Emel & Kabak, Özgür & Özaydın, Özay, 2014. "A decision support methodology to enhance the competitiveness of the Turkish automotive industry," European Journal of Operational Research, Elsevier, vol. 234(3), pages 789-801.

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