A Novel Method for Decoding Any High-Order Hidden Markov Model
This paper proposes a novel method for decoding any high-order hidden Markov model. First, the high-order hidden Markov model is transformed into an equivalent first-order hidden Markov model by Hadar’s transformation. Next, the optimal state sequence of
Fei Ye, Yifei Wang
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Research on HMM based link prediction method in heterogeneous network
In order to solve the problem that incomplete mining of structural information and semantic information in heterogeneous networks, a link prediction method combining meta-path-based analysis and hidden Markov model was proposed for link prediction of ...
Rong QIAN +4 more
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The Application of Baum-Welch Algorithm in Multistep Attack
The biggest difficulty of hidden Markov model applied to multistep attack is the determination of observations. Now the research of the determination of observations is still lacking, and it shows a certain degree of subjectivity.
Yanxue Zhang, Dongmei Zhao, Jinxing Liu
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Application of Poisson Hidden Markov Model to Predict Number of PM2.5 Exceedance Days in Tehran During 2016-2017 [PDF]
PM2.5 is an important indicator of air pollution. This pollutant can result in lung and respiratory problems in people. The aim of the present study was to predict number of PM2.5 exceedance days using Hidden Markov Model considering Poisson distribution
Fatemeh Sarvi +4 more
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Study on driver’s turning intention recognition hybrid model of GHMM and GGAP-RBF neural network
The accuracy and real time are crucial in turning intention recognition. Therefore, a hybrid model of Gaussian mixture hidden Markov and generalized growing and pruning algorithm for radial basis function neural network is constructed to recognize driver
Shu Wang, Qiang Yu, Xuan Zhao
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Real-Time Assembly Support System with Hidden Markov Model and Hybrid Extensions
This paper presents a context-aware adaptive assembly assistance system meant to support factory workers by embedding predictive capabilities. The research is focused on the predictor which suggests the next assembly step.
Arpad Gellert +4 more
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Prediksi Kurs Rupiah Terhadap Dolar Dengan FTS-Markov Chain Dan Hidden Markov Model
Hidden Markov model is a development of the Markov chain where the state cannot be observed directly (hidden), but can only be observed, a set of other observations and combination of fuzzy logic and Markov chain to predict Rupiah exchange rate against ...
Maria Titah Jatipaningrum +2 more
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fHMM: Hidden Markov Models for Financial Time Series in R
Hidden Markov models constitute a versatile class of statistical models for time series that are driven by hidden states. In financial applications, the hidden states can often be linked to market regimes such as bearish and bullish markets or ...
Lennart Oelschläger +2 more
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Error statistics of hidden Markov model and hidden Boltzmann model results
Background Hidden Markov models and hidden Boltzmann models are employed in computational biology and a variety of other scientific fields for a variety of analyses of sequential data.
Newberg Lee A
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Hidden Markov Model Based on Logistic Regression
A hidden Markov model (HMM) is a useful tool for modeling dependent heterogeneous phenomena. It can be used to find factors that affect real-world events, even when those factors cannot be directly observed.
Byeongheon Lee, Joowon Park, Yongku Kim
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