Results 211 to 220 of about 116,234 (262)

A predictive Hidden semi-Markov Model for bridges subject to chloride-induced deterioration

IEEE International Conference on Software Quality, Reliability and Security Companion, 2021
Chloride-induced deterioration is one of the main deterioration mechanisms for bridges. Directly detecting the chloride ion concentration is uneconomical for most areas.
Chunhui Guo, Zhenglin Liang, Junqi Zeng, Minyuan Song, Zongqi Xue   +4 more
semanticscholar   +1 more source

Remaining Useful Life Prediction of IIoT Equipment Using Hidden Semi-Markov Model With Hyper-Erlang Sojourn Time

IEEE Internet of Things Journal
The prediction of the remaining useful life (RUL) of equipment is a pivotal function in realizing industrial intelligence within the industrial Internet of Things (IIoT).
Xin Li, Chaoqun Duan, Jing Cai, Hongfu Zuo, Zhenzhen Liu, Yan Liu   +5 more
semanticscholar   +1 more source

A zero-inflated hidden semi-Markov model with covariate-dependent sojourn parameters for analysing marine data in the Venice lagoon

Journal of the Royal Statistical Society Series C: Applied Statistics
This paper introduces a concomitant-variable hidden semi-Markov model tailored to analyse marine count data in the Venice lagoon. Our model targets acqua alta events, i.e.
Lorena Ricciotti, Marco Picone, Alessio Pollice, A. Maruotti   +3 more
semanticscholar   +1 more source

Detecting Anomalous Behavior in Cloud Servers by Nested-Arc Hidden SEMI-Markov Model with State Summarization

IEEE Transactions on Big Data, 2019
Anomaly detection for cloud servers is important for detecting zero-day attacks. However, it is very challenging due to the large amount of accumulated data.
Waqas Haider, Jiankun Hu, Yi Xie, Xinghuo Yu, Qianhong Wu   +4 more
semanticscholar   +1 more source

Diagnosis and Prognosis of Degradation Process via Hidden Semi-Markov Model

IEEE/ASME transactions on mechatronics, 2018
The intelligent estimation of degradation state and the prediction of remaining useful life (RUL) are important for the maintenance of industrial equipment.
Tongshun Liu, K. Zhu, L. Zeng
semanticscholar   +1 more source

Fitting hidden semi-Markov models to breakpoint rainfall data

Journal of Applied Probability, 2001
The paper proposes a hidden semi-Markov model for breakpoint rainfall data that consist of both the times at which rain-rate changes and the steady rates between such changes. The model builds on and extends the seminal work of Ferguson (1980) on variable duration models for speech. For the rainfall data the observations are modelled as mixtures of log-
Peter Thomson, John Sansom
openaire   +2 more sources

Coupled Hidden Semi Markov Models for Activity Recognition

2007 IEEE Workshop on Motion and Video Computing (WMVC'07), 2007
Recognizing human activity from a stream of sensory observations is important for a number of applications such as surveillance and human-computer interaction. Hidden Markov Models (HMMs) have been proposed as suitable tools for modeling the variations in the observations for the same action and for discriminating among different actions.
Pradeep Natarajan, Ramakant Nevatia
openaire   +2 more sources

Hidden semi-Markov models for electricity load disaggregation

ACM SIGMETRICS Performance Evaluation Review, 2019
This paper assesses the performance of a technique for estimating the power consumption of individual devices based on aggregate consumption. The new semi-Markov technique, outperforms pure hidden Markov models on the REDD dataset. The technique also exploits information from transients to eliminate a substantial fraction of the observed ...
Yung Fei Wong, Y. Ahmet Sekercioglu, Lachlan L. H. Andrew   +2 more
openaire   +1 more source

On efficient Viterbi decoding for hidden semi-Markov models

2008 19th International Conference on Pattern Recognition, 2008
We present algorithms for improved Viterbi decoding for the case of hidden semi-Markov models. By carefully constructing directed acyclic graphs, we pose the decoding problem as that of finding the longest path between specific pairs of nodes. We consider fully connected models as well as restrictive topologies and state duration conditions, and show ...
Bonnie K. Ray, Jianying Hu, Ritendra Datta   +2 more
openaire   +2 more sources

Offline and online identification of hidden semi-Markov models

IEEE Transactions on Signal Processing, 2005
We present a new signal model for hidden semi-Markov models (HSMMs). Instead of constant transition probabilities used in existing models, we use state-duration-dependant transition probabilities. We show that our modeling approach leads to easy and efficient implementation of parameter identification algorithms.
Maryam Azimi, Rabab K. Ward, Panos Nasiopoulos   +2 more
openaire   +2 more sources