Input-Output Hidden Markov Model for Diagnosis of Complex System. Shahin, K. I., Simon, C., & Weber, P. In June, 2019.
abstract   bibtex   
Prognosis system state of degradation and estimating its remaining useful life requires the system health assessment. For a correct prognostic, a good diagnostic as health assessment is required. Complex systems are difficult to manage for modeling reasons considering complexity, environmental and operational conditions. This paper deals with a stochastic model for generic modeling purposes and considers operating conditions in order to determine the system health. The proposed model is an Input-Output Hidden Markov Model that is able to model a degradation process of complex systems given operational conditions and allows assessing the system health. Well-known algorithms dedicated to HMM are adapted to IOHMM for multiple observation sequences and inputs.
@inproceedings{shahin_input-output_2019,
	title = {Input-{Output} {Hidden} {Markov} {Model} for {Diagnosis} of {Complex} {System}},
	abstract = {Prognosis system state of degradation and estimating its remaining useful life requires the system health assessment. For a correct prognostic, a good diagnostic as health assessment is required. Complex systems are difficult to manage for modeling reasons considering complexity, environmental and operational conditions. This paper deals with a stochastic model for generic modeling purposes and considers operating conditions in order to determine the system health. The proposed model is an Input-Output Hidden Markov Model that is able to model a degradation process of complex systems given operational conditions and allows assessing the system health. Well-known algorithms dedicated to HMM are adapted to IOHMM for multiple observation sequences and inputs.},
	author = {Shahin, Kamrul Islam and Simon, Christophe and Weber, Philippe},
	month = jun,
	year = {2019},
}

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