Metraipolis › archive › dc_39c693da4e49

Optimizing Gaussian process regression (GPR) hyperparameters with three metaheuristic algorithms for viscosity prediction of suspensions containing… — Europe PMC PMID:39217234

Source: Europe PMC (en)
Original: https://europepmc.org/article/MED/39217234
DOI: 10.1038/s41598-[numero omesso]-9
License (as archived): solo-consultazione
Archived: 2026-10-08T05:36:44.355Z
SHA-256 of the archived text: 8a44fb3cc15253085d572753faae25d73ba8b68ff0612ef0c0ff0cb76ec497ce
Stable URL of this page: https://metraipolis.com/documento/dc_39c693da4e49

How to cite

Optimizing Gaussian process regression (GPR) hyperparameters with three metaheuristic algorithms for viscosity prediction of suspensions containing… — Europe PMC PMID:39217234 — Europe PMC (en), https://europepmc.org/article/MED/39217234 (solo-consultazione); archived copy: https://metraipolis.com/documento/dc_39c693da4e49 (Metraipolis archive dc_39c693da4e49, sha256 8a44fb3cc15253085d572753faae25d73ba8b68ff0612ef0c0ff0cb76ec497ce)

BibTeX

@misc{dc39c693da4e49,
  title = {Optimizing Gaussian process regression (GPR) hyperparameters with three metaheuristic algorithms for viscosity prediction of suspensions containing… — Europe PMC PMID:39217234},
  howpublished = {Europe PMC (en)},
  url = {https://europepmc.org/article/MED/39217234},
  note = {License solo-consultazione; archived copy https://metraipolis.com/documento/dc_39c693da4e49; sha256 8a44fb3cc15253085d572753faae25d73ba8b68ff0612ef0c0ff0cb76ec497ce},
  year = {2026}
}

Archived text

The text is not reproduced here: the archive holds it as solo-consultazione (consultation only, no republication). Read it at the original source: https://europepmc.org/article/MED/39217234. Agents can read the archived copy with the MCP tool read_document.