Area-specific predictions of unwanted events using multivariate modeling of water data

Katarina Nielsen Dominiak; Jeff Hindsborg; Lene Juul Pedersen; Anders Ringgaard Kristensen

Area-specific predictions of unwanted events using multivariate modeling of water data

Katarina Nielsen Dominiak, Jeff Hindsborg, Lene Juul Pedersen, Anders Ringgaard Kristensen

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Abstract

In this study simultaneously monitored drinking patterns from multiple pens in one weaner section and one finisher section herd are modeled in a multivariate dynamic linear model (DLM). Correlations between the monitored data are incorporated in the model allowing it to include interactions between pens in each section. A two-sided tabular CUSUM is applied as control chart, whereby alarms for outbreaks of unwanted events amongst the pigs can be generated for specific pens in the herd. Area-specific alarms enable the manager to include specific knowledge of the animals in the targeted area and choose the best suited intervention.

Originalsprog	Engelsk
Publikationsdato	12 jul. 2018
Status	Udgivet - 12 jul. 2018
Begivenhed	2nd International Conference on Agro Big Data and Decision Support Systems in Agriculture - Universitat de Lleida, Lleida, Spanien Varighed: 12 jul. 2018 → 14 jul. 2018 Konferencens nummer: 2 http://www.bigdssagro.udl.cat/congreso2018/?q=presentation

Konference

Konference	2nd International Conference on Agro Big Data and Decision Support Systems in Agriculture
Nummer	2
Lokation	Universitat de Lleida
Land/Område	Spanien
By	Lleida
Periode	12/07/2018 → 14/07/2018
Internetadresse	http://www.bigdssagro.udl.cat/congreso2018/?q=presentation

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Proceedings_Lleida_bigDSSagro2018Forlagets udgivne version, 58 KBLicens: Ikke-specificeret

Citationsformater

Area-specific predictions of unwanted events using multivariate modeling of water data. / Dominiak, Katarina Nielsen; Hindsborg, Jeff; Pedersen, Lene Juul et al.
2018. 27-30 Afhandling præsenteret på 2nd International Conference on Agro Big Data and Decision Support Systems in Agriculture, Lleida, Spanien.

Publikation: Konferencebidrag › Paper › Forskning › peer review

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abstract = "In this study simultaneously monitored drinking patterns from multiple pens in one weaner section and one finisher section herd are modeled in a multivariate dynamic linear model (DLM). Correlations between the monitored data are incorporated in the model allowing it to include interactions between pens in each section. A two-sided tabular CUSUM is applied as control chart, whereby alarms for outbreaks of unwanted events amongst the pigs can be generated for specific pens in the herd. Area-specific alarms enable the manager to include specific knowledge of the animals in the targeted area and choose the best suited intervention.",

author = "Dominiak, {Katarina Nielsen} and Jeff Hindsborg and Pedersen, {Lene Juul} and Kristensen, {Anders Ringgaard}",

note = "Proceedings of the Second International Conference on Agro Big Data and Decision Support Systems in Agriculture. ISBN: 978-84-09-04920-2.; 2nd International Conference on Agro Big Data and Decision Support Systems in Agriculture ; Conference date: 12-07-2018 Through 14-07-2018",

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AU - Pedersen, Lene Juul

AU - Kristensen, Anders Ringgaard

N1 - Conference code: 2

PY - 2018/7/12

Y1 - 2018/7/12

N2 - In this study simultaneously monitored drinking patterns from multiple pens in one weaner section and one finisher section herd are modeled in a multivariate dynamic linear model (DLM). Correlations between the monitored data are incorporated in the model allowing it to include interactions between pens in each section. A two-sided tabular CUSUM is applied as control chart, whereby alarms for outbreaks of unwanted events amongst the pigs can be generated for specific pens in the herd. Area-specific alarms enable the manager to include specific knowledge of the animals in the targeted area and choose the best suited intervention.

AB - In this study simultaneously monitored drinking patterns from multiple pens in one weaner section and one finisher section herd are modeled in a multivariate dynamic linear model (DLM). Correlations between the monitored data are incorporated in the model allowing it to include interactions between pens in each section. A two-sided tabular CUSUM is applied as control chart, whereby alarms for outbreaks of unwanted events amongst the pigs can be generated for specific pens in the herd. Area-specific alarms enable the manager to include specific knowledge of the animals in the targeted area and choose the best suited intervention.

M3 - Paper

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T2 - 2nd International Conference on Agro Big Data and Decision Support Systems in Agriculture

Y2 - 12 July 2018 through 14 July 2018

ER -

Area-specific predictions of unwanted events using multivariate modeling of water data

Abstract

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