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dc.contributor.authorPontin, David R.en
dc.contributor.authorWatts, Michael J.en
dc.contributor.authorWorner, Susan P.en
dc.date.accessioned2010-06-14T02:38:56Z
dc.date.issued2008-06en
dc.identifier.citationPontin, D. R., Watts, M. J., & Worner, S. P. (2008). Using multi-layer perceptrons to predict the presence of jellyfish of the genus Physalia at New Zealand beaches. In IEEE International Joint Conference on Neural Networks, 2008 (pp. 1170-1175). Piscataway, NJ: IEEE.en
dc.identifier.isbn978-1-4244-1820-6en
dc.identifier.issn1098-7576en
dc.identifier.urihttps://hdl.handle.net/10182/2058
dc.description.abstractThe 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.en
dc.format.extent1170-1175en
dc.language.isoenen
dc.publisherIEEEen
dc.relationThe original publication is available from - IEEE - https://doi.org/10.1109/IJCNN.2008.4633947en
dc.relation.urihttps://doi.org/10.1109/IJCNN.2008.4633947en
dc.rights© 2008 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.en
dc.sourceIEEE International Joint Conference on Neural Networksen
dc.subjectmultilayer perceptronen
dc.subjectPhysaliaen
dc.subjectjellyfishen
dc.subjectbeachesen
dc.subjectNew Zealanden
dc.subjectoceanographic dataen
dc.subjectartificial neural networksen
dc.titleUsing multi-layer perceptrons to predict the presence of jellyfish of the genus Physalia at New Zealand beachesen
dc.typeConference Contribution - Published
lu.contributor.unitLincoln Universityen
lu.contributor.unitBio-Protection and Ecologyen
lu.contributor.unitBio-Protection Research Centreen
dc.identifier.doi10.1109/IJCNN.2008.4633947en
pubs.finish-date2008-06-08en
pubs.organisational-group/LU
pubs.organisational-group/LU/BPEC
pubs.organisational-group/LU/BPRC
pubs.publication-statusPublisheden
pubs.start-date2008-06-01en
lu.subtypeConference Paperen


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