Zobrazeno 1 - 5
of 5
pro vyhledávání: '"Narendhar Gugulothu"'
Publikováno v:
International Journal of Prognostics and Health Management, Vol 9, Iss 1 (2018)
We consider the problem of estimating the remaining useful life (RUL) of a system or a machine from sensor data. Many approaches for RUL estimation based on sensor data make assumptions about how machines degrade. Additionally, sensor data from machi
Externí odkaz:
https://doaj.org/article/3da47e6e55114cb28967e6ba219f32a7
Publikováno v:
Lecture Notes in Computer Science ISBN: 9783030304836
ICANN (2)
ICANN (2)
Accurate forecasting of a high variability time series has relevance in many applications such as supply-chain management, price prediction in stock markets and demand forecasting in the energy segment. Most often forecasts of such time series depend
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::1ba2f23e6e50553afcd7fe0520325406
https://doi.org/10.1007/978-3-030-30484-3_35
https://doi.org/10.1007/978-3-030-30484-3_35
Autor:
Narendhar Gugulothu, Vishnu Tv, Lovekesh Vig, Puneet Agarwal, Gautam Shroff, Priyanka Gupta, Pankaj Malhotra
Publikováno v:
Annual Conference of the PHM Society. 10
In this work, we attempt to address two practical limitations when using Recurrent Neural Networks (RNNs) as classifiers for fault detection using multi-sensor time series data: Firstly, there is a need to understand the classification decisions of R
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::485653dde6a28d1fcebdd06c8b8c5a9b
https://doi.org/10.36001/phmconf.2018.v10i1.468
https://doi.org/10.36001/phmconf.2018.v10i1.468
Autor:
Sakti Saurav, Narendhar Gugulothu, Gautam Shroff, Pankaj Malhotra, Lovekesh Vig, Vishnu Tv, Puneet Agarwal
Publikováno v:
COMAD/CODS
Anomaly detection in time series is an important task with several practical applications. The common approach of training one model in an offline manner using historical data is likely to fail under dynamically changing and non-stationary environmen
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::e05ad111ecd01be9605d0a31424f82c8
https://doi.org/10.1145/3152494.3152501
https://doi.org/10.1145/3152494.3152501
Publikováno v:
International Journal of Prognostics and Health Management, Vol 9, Iss 1 (2018)
We consider the problem of estimating the remaining useful life (RUL) of a system or a machine from sensor data. Many approaches for RUL estimation based on sensor data make assumptions about how machines degrade. Additionally, sensor data from machi
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::94dd6ebd924992d9b3546254c200112b
http://arxiv.org/abs/1709.01073
http://arxiv.org/abs/1709.01073