Rhino poaching in South Africa is leading to a catastrophic reduction in the rhino population. In this paper a Bayesian network causal model is proposed to model the underlying (causal) relationships that lead to rhino poaching events. The model may be used to fuse a collection of heterogeneous information sources. If a game reserve is partitioned into several geographical areas or cells, the model may perform inference for each of these cells separately, and give a relative predictive distribution of poaching events over the game reserve. After an overview of the current problem definition and a brief overview of similar modelling approaches, the Bayesian network model is presented. The developed Bayesian network based model is an initial attempt at proposing a sensible modelling approach for this problem. Some of the complexities of the approach are discussed, before considering how the model may be validated at a later stage.
Reference:
Koen, H, De Villiers, J.P, Pavlin, G, De Waal, A, De Oude, P and Mignet, F. 2014. A framework for inferring predictive distributions of rhino poaching events through causal modelling. In: FUSION 2014, Salamanca, Spain, 7-10 July 2014
Koen, H., De Villiers, J., Pavlin, G., De Waal, A., De Oude, P., & Mignet, F. (2014). A framework for inferring predictive distributions of rhino poaching events through causal modelling. http://hdl.handle.net/10204/7631
Koen, H, JP De Villiers, G Pavlin, A De Waal, P De Oude, and F Mignet. "A framework for inferring predictive distributions of rhino poaching events through causal modelling." (2014): http://hdl.handle.net/10204/7631
Koen H, De Villiers J, Pavlin G, De Waal A, De Oude P, Mignet F, A framework for inferring predictive distributions of rhino poaching events through causal modelling; 2014. http://hdl.handle.net/10204/7631 .
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