Results 31 to 40 of about 116,234 (262)
Heavy tailed hidden semi-markov models [PDF]
Communications in Statistics. Stochastic Models, 1998 Summary: Hidden semi-Markov models have been proposed by \textit{K. S. Meier-Hellstern}, \textit{P. E. Wirth}, \textit{Y. L. Yan} and \textit{D. A. Hoeflin} [in: Teletraffic and datatraffic in a period of change (A. Jensen and V. B. Iversen (eds.)), 167-192 (1991)] to model the times between transmission of packets at a source.
Resnick, S., Subramanian, A.
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Hidden Semi-Markov Models for Predictive Maintenance [PDF]
Mathematical Problems in Engineering, 2015 Realistic predictive maintenance approaches are essential for condition monitoring and predictive maintenance of industrial machines. In this work, we propose Hidden Semi-Markov Models (HSMMs) with (i) no constraints on the state duration density function and (ii) being applied to continuous or discrete observation. To deal with such a type of HSMM, we
Francesco Cartella +3 more
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Proceedings of the International Florida Artificial Intelligence Research Society Conference, 2021 Hidden Markov model (HMM) has been a popular choice for financial time series modeling due to its advantage in capturing dynamic regimes. However, HMM's implicit assumption that the state duration follows a geometric distribution is too strong to hold in
Zekun Xu, Ye Liu
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Improving Phoneme Sequence Recognition using Phoneme Duration Information in DNN-HSMM [PDF]
Journal of Artificial Intelligence and Data Mining, 2019 Improving phoneme recognition has attracted the attention of many researchers due to its applications in various fields of speech processing. Recent research achievements show that using deep neural network (DNN) in speech recognition systems ...
M. Asadolahzade Kermanshahi +1 more
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Prediction of PM2.5 pollution in Tehran air based on temperature and pressure using Markovian regime-switching non-parametric additive transitive regression model [PDF]
ریاضی و جامعه, 2023 In this paper, we introduce the Markovian regime-switching regression model, which is a graphical model based on the hidden Markov model. This model can be viewed as a clustered regression model, in which a Markov process models the transition from one ...
Morteza Amini
doaj +1 more source
Target Location Method Based on Compressed Sensing in Hidden Semi Markov Model
Electronics, 2022 A compressive sensing-based target localization method based on hidden semi-Markov model (HsMM) is proposed to address problems like unpredictable data and the multipath effect of the Receive Signal Strength (RSS) in indoor localization.
Xin Tian, Guoliang Wei, Jianhua Wang
semanticscholar +1 more source
Hidden Markov models: the best models for forager movements? [PDF]
PLoS ONE, 2013 One major challenge in the emerging field of movement ecology is the inference of behavioural modes from movement patterns. This has been mainly addressed through Hidden Markov models (HMMs).
Rocio Joo +3 more
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From Risk Assessment to Resilience Assessment. an Application to a Hazmat Storage Plant
Chemical Engineering Transactions, 2020 The purpose of this work is to outline a framework for assessing the resilience of a petrochemical storage plant, through the construction of a dynamic hierarchical Bayesian network. The BN approach allows keeping memory of the states, in order to manage
Tomaso Vairo +2 more
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Hidden Markov Model and States Prediction of an Autonomous Wind-Diesel Complex [PDF]
E3S Web of Conferences, 2023 The problem of assessing the reliability and analyzing the functioning of an autonomous winddiesel complex, consisting of a wind power plant, working and standby diesel generators, an inverter and a storage battery, is considered.
Obzherin Yuriy E. +2 more
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Flexible and practical modeling of animal telemetry data: hidden Markov models and extensions [PDF]
, 2012 We discuss hidden Markov-type models for fitting a variety of multistate random walks to wildlife movement data. Discrete-time hidden Markov models (HMMs) achieve considerable computational gains by focusing on observations that are regularly spaced in ...
Langrock, R. +5 more
core +3 more sources