Forecasting Obsolescence of Components by Using a Clustering-Based Hybrid Machine-Learning Algorithm
- DOI
- 10.3390/s22093244
- Published
- 2022-04-23
- Container
- Sensors
- Publisher
- MDPI AG
- Open access
- unknown
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Cite this work
BibTeX
@article{allodium:10.3390/s22093244,
title = {Forecasting Obsolescence of Components by Using a Clustering-Based Hybrid Machine-Learning Algorithm},
author = {Kyoung-Sook Moon and Hee Won Lee and Hee Jean Kim and Hongjoong Kim and Jeehoon Kang and Won Chul Paik},
year = {2022},
journal = {Sensors},
doi = {10.3390/s22093244},
url = {https://doi.org/10.3390/s22093244}
}RIS
TY - JOUR TI - Forecasting Obsolescence of Components by Using a Clustering-Based Hybrid Machine-Learning Algorithm AU - Kyoung-Sook Moon AU - Hee Won Lee AU - Hee Jean Kim AU - Hongjoong Kim AU - Jeehoon Kang AU - Won Chul Paik PY - 2022 JO - Sensors DO - 10.3390/s22093244 UR - https://doi.org/10.3390/s22093244 ER -
APA
Moon, K., Lee, H. W., Kim, H. J., Kim, H., Kang, J., & Paik, W. C. (2022). Forecasting Obsolescence of Components by Using a Clustering-Based Hybrid Machine-Learning Algorithm. Sensors. https://doi.org/10.3390/s22093244
Source records
- crossref · retrieved 2026-11-10T07:34:25.762Z