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

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

Date Submitted: 2023-08-18

Identifier
DOI	https://doi.org/10.17026/DANS-29S-TMJ7
Metadata Access	https://phys-techsciences.datastations.nl/oai?verb=GetRecord&metadataPrefix=oai_datacite&identifier=doi:10.17026/DANS-29S-TMJ7

Provenance
Creator	Z. Wang
Publisher	DANS Data Station Physical and Technical Sciences
Contributor	Data Librarian; H.J. van der Fels Klerx (Wageningen University & Research); A.G.J.M. Oude Lansink (Wageningen University & Research); Wageningen University & Research
Publication Year	2023
Rights	CC-BY-4.0; info:eu-repo/semantics/openAccess; http://creativecommons.org/licenses/by/4.0
OpenAccess	true
Contact	Data Librarian (Wageningen UR)

Representation
Resource Type	Dataset
Format	type/x-r-syntax; text/tab-separated-values; application/zip; text/plain
Size	22357; 10185; 24342; 10242; 17481; 12192; 11849; 4055
Version	1.0
Discipline	Agriculture, Forestry, Horticulture, Aquaculture; Agriculture, Forestry, Horticulture, Aquaculture and Veterinary Medicine; Chemistry; Food Safety; Life Sciences; Natural Sciences