We apply machine learning techniques to the synthetic data (Stevens and Anderson-Cook, 2017a), which is univariate data with a binary response of passing or failing for complex munitions generated to match age and usage rate, found in US Department of Defense complex systems (the army and navy). We propose applying machine learning techniques to predict the binary response of passing or failing for the army and navy data.
|Original language||English (US)|
|Number of pages||18|
|Journal||International Journal of Productivity and Quality Management|
|State||Published - 2020|
Bibliographical noteFunding Information:
This research was supported by Basic Science Research Program through the National Research Foundation of Korea (NRF) funded by the Ministry of Education (No. NRF-2017R1E1A1A03070747).
- Artificial neural networks
- Binary response data
- Elastic net