Predicting Remaining Useful Life Based on the Failure Time Data with Heavy-Tailed Behavior and User Usage Patterns Using Proportional Hazards Model

Zhiguo Li, Gregory Kott. Predicting Remaining Useful Life Based on the Failure Time Data with Heavy-Tailed Behavior and User Usage Patterns Using Proportional Hazards Model. In Sorin Draghici, Taghi M. Khoshgoftaar, Vasile Palade, Witold Pedrycz, M. Arif Wani, Xingquan Zhu, editors, The Ninth International Conference on Machine Learning and Applications, ICMLA 2010, Washington, DC, USA, 12-14 December 2010. pages 623-628, IEEE Computer Society, 2010. [doi]

@inproceedings{LiK10-15,
  title = {Predicting Remaining Useful Life Based on the Failure Time Data with Heavy-Tailed Behavior and User Usage Patterns Using Proportional Hazards Model},
  author = {Zhiguo Li and Gregory Kott},
  year = {2010},
  doi = {10.1109/ICMLA.2010.96},
  url = {http://dx.doi.org/10.1109/ICMLA.2010.96},
  researchr = {https://researchr.org/publication/LiK10-15},
  cites = {0},
  citedby = {0},
  pages = {623-628},
  booktitle = {The Ninth International Conference on Machine Learning and Applications, ICMLA 2010, Washington, DC, USA, 12-14 December 2010},
  editor = {Sorin Draghici and Taghi M. Khoshgoftaar and Vasile Palade and Witold Pedrycz and M. Arif Wani and Xingquan Zhu},
  publisher = {IEEE Computer Society},
  isbn = {978-0-7695-4300-0},
}