Abstract
The proportional intensity model (PIM) has been used to model the intensity function of repairable systems taking non-time factors, such as operating conditions, and repair history, into consideration. This paper develops a kernelized PIM (KPIM) by combining the PIM and the kernel method to consider a scenario where a repairable system experiences piecewise operating conditions. The kernel method is used to approximate the PIM covariate function nonlinearly. An approach based on the regularized likelihood function is proposed to obtain the optimal parameters for the KPIM. A numerical example is provided to demonstrate the KPIM model, and the parameter estimation approach.
Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
