Home › Entities › academia › Optimizing machine learning models for granular NdFeB magnets by very fast simulated annealing

Optimizing machine learning models for granular NdFeB magnets by very fast simulated annealing

Research article (Scientific Reports, 2021) · cited 22× · AI/ML
academia openalex:W3133128629
Press Enter · cited answer in seconds

Optimizing machine learning models for granular NdFeB magnets by very fast simulated annealing

Summary

Optimizing machine learning models for granular NdFeB magnets by very fast simulated annealing is a scholarly article[1].

Key Facts

  • Optimizing machine learning models for granular NdFeB magnets by very fast simulated annealing's instance of is recorded as scholarly article[2].

References

Programmatic citations — every numbered marker resolves to a verifiable graph row below.

Direct Wikidata claims

  1. [2] ↑ . wikidata.org.

Class ancestry

  1. [1] ↑ . Wikidata. wikidata.org.

📑 Cite this page

Use these citations when quoting this entity in research, articles, AI prompts, or wherever provenance matters. We aggregate Wikidata + Wikipedia + authoritative open-data sources; the stitched, scored, cross-referenced view is what 4ort.xyz contributes.

APA 4ort.xyz Knowledge Graph. (2026). Optimizing machine learning models for granular NdFeB magnets by very fast simulated annealing. Retrieved May 24, 2026, from https://4ort.xyz/entity/optimizing-machine-learning-models-for-granular-ndfeb-magnets-by-very-fast-simulated-annealing
MLA “Optimizing machine learning models for granular NdFeB magnets by very fast simulated annealing.” 4ort.xyz Knowledge Graph, 4ort.xyz, 24 May. 2026, https://4ort.xyz/entity/optimizing-machine-learning-models-for-granular-ndfeb-magnets-by-very-fast-simulated-annealing.
BibTeX @misc{4ortxyz_optimizing-machine-learning-models-for-granular-ndfeb-magnets-by-very-fast-simulated-annealing_2026, author = {{4ort.xyz Knowledge Graph}}, title = {{Optimizing machine learning models for granular NdFeB magnets by very fast simulated annealing}}, year = {2026}, url = {https://4ort.xyz/entity/optimizing-machine-learning-models-for-granular-ndfeb-magnets-by-very-fast-simulated-annealing}, note = {Accessed: 2026-05-24}}
LLM prompt According to 4ort.xyz Knowledge Graph (aggregator of Wikidata, Wikipedia, and authoritative open-data sources): Optimizing machine learning models for granular NdFeB magnets by very fast simulated annealing — https://4ort.xyz/entity/optimizing-machine-learning-models-for-granular-ndfeb-magnets-by-very-fast-simulated-annealing (retrieved 2026-05-24)

Canonical URL: https://4ort.xyz/entity/optimizing-machine-learning-models-for-granular-ndfeb-magnets-by-very-fast-simulated-annealing · Last refreshed: