Bayesian Network Modelling Association

The BNMA BN Repository

This repository is a resource for posting and downloading Bayesian network models for sharing with others and for providing supporting material for publications. Please respect authors' rights where noted.

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3 BNs found.

Arhopalus Flight Activity

This Bayesian network was developed to model the flight activity of Arhopalus ferus, a wood borer. The model is used to predict flight activity as a function of meteorological conditions. This contributes to the quantification of potential phytosanitary risks as it is a measure of potential exposure of export logs to flying/dispersing insects.

The data set for this model can be found at <abnms.org...>.

Pawson, S.M., Marcot, B.G., Woodberry, O.G
Netica .dne format
Pawson, S.M., Marcot, B.G. & Woodberry, O.G. (2017) Predicting forest insect flight activity: A Bayesian network approach. PloS one, 12(9):e0183464, Public Library of Science
Biology > Ecology
Hylastes Flight Activity

This Bayesian network was developed to model the flight activity of Hylastes ater, a bark beetle. The model is used to predict flight activity as a function of meteorological conditions. This contributes to the quantification of potential phytosanitary risks as it is a measure of potential exposure of export logs to flying/dispersing insects.

The data set for this model can be found at <abnms.org...>.

Pawson, S.M., Marcot, B.G., Woodberry, O.G
Netica .dne format
Pawson, S.M., Marcot, B.G. & Woodberry, O.G. (2017) Predicting forest insect flight activity: A Bayesian network approach. PloS one, 12(9):e0183464, Public Library of Science
Biology > Ecology
Hylurgus Flight Activity

This Bayesian network was developed to model the flight activity of Hylurgus ligniperda as a function of meteorological conditions. H. ligniperda is a common forest insect within New Zealand Pinus radiata plantations forests. Predicting flight activity is one step towards assessing potential phytosanitary risks of forest exports as it is an indication of the exposure of logs to flying/dispersing insects.

The data set for this model can be found at <abnms.org...>.

Pawson, S.M., Marcot, B.G., Woodberry, O.W.
Netica .dne format
Pawson, S.M., Marcot, B.G. & Woodberry, O.G. (2017) Predicting forest insect flight activity: A Bayesian network approach. PloS one, 12(9):e0183464, Public Library of Science
Biology > Ecology