Root cause prediction for failures in semiconductor industry, a genetic algorithm-machine learning approach.
- DOI
- 10.1038/s41598-023-30769-8
- Published
- 2023 Mar 27
- Container
- Scientific reports
- Publisher
- Not recorded
- Open access
- yes
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limited evidence Score 45/100 under policy 1.0.0. This is a metadata assessment, not a judgment of the paper's conclusions.
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Cite this work
BibTeX
@article{allodium:10.1038/s41598-023-30769-8,
title = {Root cause prediction for failures in semiconductor industry, a genetic algorithm-machine learning approach.},
author = {Rammal A and Ezukwoke K and Hoayek A and Batton-Hubert M},
year = {2023},
journal = {Scientific reports},
doi = {10.1038/s41598-023-30769-8},
url = {https://doi.org/10.1038/s41598-023-30769-8}
}RIS
TY - JOUR TI - Root cause prediction for failures in semiconductor industry, a genetic algorithm-machine learning approach. AU - Rammal A AU - Ezukwoke K AU - Hoayek A AU - Batton-Hubert M PY - 2023 JO - Scientific reports DO - 10.1038/s41598-023-30769-8 UR - https://doi.org/10.1038/s41598-023-30769-8 ER -
APA
A, R., K, E., A, H., & M, B. (2023). Root cause prediction for failures in semiconductor industry, a genetic algorithm-machine learning approach.. Scientific reports. https://doi.org/10.1038/s41598-023-30769-8
Source records
- pubmed · retrieved 2026-09-25T20:51:32.594Z