Recurrent neural networks for remaining useful life estimation. Heimes, F. O. In 2008 International Conference on Prognostics and Health Management, pages 1–6, 2008. ISSN: nulldoi bibtex @inproceedings{heimes_recurrent_2008,
title = {Recurrent neural networks for remaining useful life estimation},
doi = {10.1109/PHM.2008.4711422},
booktitle = {2008 {International} {Conference} on {Prognostics} and {Health} {Management}},
author = {Heimes, F. O.},
year = {2008},
note = {ISSN: null},
keywords = {Degradation, Kalman filters, Life estimation, Machine Learning, Machine learning, Machine learning algorithms, Management training, Pollution measurement, Prognostics, Prognostics and health management, Recurrent Neural Networks, Recurrent neural networks, Remaining Useful Life, Statistics, Testing, back-propagation, evolutionary algorithms, evolutionary computation, extended Kalman Filter training method, learning (artificial intelligence), machine learning, nonlinear filters, recurrent neural nets, recurrent neural networks, remaining useful life estimation},
pages = {1--6},
}
Downloads: 0
{"_id":"TpCjPup9c9p4FHALG","bibbaseid":"heimes-recurrentneuralnetworksforremainingusefullifeestimation-2008","author_short":["Heimes, F. O."],"bibdata":{"bibtype":"inproceedings","type":"inproceedings","title":"Recurrent neural networks for remaining useful life estimation","doi":"10.1109/PHM.2008.4711422","booktitle":"2008 International Conference on Prognostics and Health Management","author":[{"propositions":[],"lastnames":["Heimes"],"firstnames":["F.","O."],"suffixes":[]}],"year":"2008","note":"ISSN: null","keywords":"Degradation, Kalman filters, Life estimation, Machine Learning, Machine learning, Machine learning algorithms, Management training, Pollution measurement, Prognostics, Prognostics and health management, Recurrent Neural Networks, Recurrent neural networks, Remaining Useful Life, Statistics, Testing, back-propagation, evolutionary algorithms, evolutionary computation, extended Kalman Filter training method, learning (artificial intelligence), machine learning, nonlinear filters, recurrent neural nets, recurrent neural networks, remaining useful life estimation","pages":"1–6","bibtex":"@inproceedings{heimes_recurrent_2008,\n\ttitle = {Recurrent neural networks for remaining useful life estimation},\n\tdoi = {10.1109/PHM.2008.4711422},\n\tbooktitle = {2008 {International} {Conference} on {Prognostics} and {Health} {Management}},\n\tauthor = {Heimes, F. O.},\n\tyear = {2008},\n\tnote = {ISSN: null},\n\tkeywords = {Degradation, Kalman filters, Life estimation, Machine Learning, Machine learning, Machine learning algorithms, Management training, Pollution measurement, Prognostics, Prognostics and health management, Recurrent Neural Networks, Recurrent neural networks, Remaining Useful Life, Statistics, Testing, back-propagation, evolutionary algorithms, evolutionary computation, extended Kalman Filter training method, learning (artificial intelligence), machine learning, nonlinear filters, recurrent neural nets, recurrent neural networks, remaining useful life estimation},\n\tpages = {1--6},\n}\n\n\n\n","author_short":["Heimes, F. O."],"key":"heimes_recurrent_2008","id":"heimes_recurrent_2008","bibbaseid":"heimes-recurrentneuralnetworksforremainingusefullifeestimation-2008","role":"author","urls":{},"keyword":["Degradation","Kalman filters","Life estimation","Machine Learning","Machine learning","Machine learning algorithms","Management training","Pollution measurement","Prognostics","Prognostics and health management","Recurrent Neural Networks","Recurrent neural networks","Remaining Useful Life","Statistics","Testing","back-propagation","evolutionary algorithms","evolutionary computation","extended Kalman Filter training method","learning (artificial intelligence)","machine learning","nonlinear filters","recurrent neural nets","recurrent neural networks","remaining useful life estimation"],"metadata":{"authorlinks":{}},"html":""},"bibtype":"inproceedings","biburl":"https://bibbase.org/zotero/mh_lenguyen","dataSources":["iwKepCrWBps7ojhDx"],"keywords":["degradation","kalman filters","life estimation","machine learning","machine learning","machine learning algorithms","management training","pollution measurement","prognostics","prognostics and health management","recurrent neural networks","recurrent neural networks","remaining useful life","statistics","testing","back-propagation","evolutionary algorithms","evolutionary computation","extended kalman filter training method","learning (artificial intelligence)","machine learning","nonlinear filters","recurrent neural nets","recurrent neural networks","remaining useful life estimation"],"search_terms":["recurrent","neural","networks","remaining","useful","life","estimation","heimes"],"title":"Recurrent neural networks for remaining useful life estimation","year":2008}