Using multi-layer perceptrons to predict the presence of jellyfish of the genus Physalia at New Zealand beaches
The apparent increase in number and magnitude of jellyfish blooms in the world's oceans has lead to concerns over potential disruption and harm to global fishery stocks. Because of the potential harm that jellyfish populations can cause and to avoid impact it would be helpful to model jellyfish populations so that species presence or absence can be predicted. Data on the presence or absence of jellyfish of the genus Physalia was modelled using multi-layer perceptrons (MLP) based on oceanographic data. Results indicated that MLP are capable of predicting the presence or absence of Physalia in two regions in New Zealand and of identifying significant biological variables.... [Show full abstract]
Keywordsmultilayer perceptron; Physalia; jellyfish; beaches; New Zealand; oceanographic data; artificial neural networks
TypeConference Contribution - published (Conference Paper)
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