Designing optimal food safety monitoring schemes using Bayesian network and Integer programming: the case of dioxins and DL-PCBs monitoring - Dataset - B2FIND

Dataset

Designing optimal food safety monitoring schemes using Bayesian network and Integer programming: the case of dioxins and DL-PCBs monitoring

DOI PID

Bayesian Network was applied to estimate probability of contamination occurrence. Linear programming was used to optimize monitoring based on estimated probabilities.

Identifier
DOI	https://doi.org/10.17026/dans-29s-tmj7
PID	https://nbn-resolving.org/urn:nbn:nl:ui:13-s3-ay8f
Related Identifier	https://doi.org/10.4121/c.5678509
Metadata Access	https://easy.dans.knaw.nl/oai?verb=GetRecord&metadataPrefix=oai_datacite&identifier=oai:easy.dans.knaw.nl:easy-dataset:316016

Provenance
Creator	Wang, Z.
Publisher	Wageningen University & Research
Contributor	Fels Klerx, H.J. van der; Oude Lansink, A.G.J.M.; Wageningen University & Research
Publication Year	2023
Rights	info:eu-repo/semantics/openAccess; License: http://creativecommons.org/licenses/by/4.0; http://creativecommons.org/licenses/by/4.0
OpenAccess	true

Representation
Language	English
Resource Type	Dataset
Format	text/plain; .xlsx; .R
Discipline	Agriculture, Forestry, Horticulture, Aquaculture; Agriculture, Forestry, Horticulture, Aquaculture and Veterinary Medicine; Chemistry; Food Safety; Life Sciences; Natural Sciences