{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2024,10,29]],"date-time":"2024-10-29T10:41:00Z","timestamp":1730198460482,"version":"3.28.0"},"reference-count":25,"publisher":"IEEE","content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2017,12]]},"DOI":"10.1109\/ascc.2017.8287391","type":"proceedings-article","created":{"date-parts":[[2018,2,14]],"date-time":"2018-02-14T20:30:38Z","timestamp":1518640238000},"page":"1476-1481","source":"Crossref","is-referenced-by-count":1,"title":["Recurrent neural network-based fault detector for aileron failures of aircraft"],"prefix":"10.1109","author":[{"given":"Nobuyuki","family":"Yoshikawa","sequence":"first","affiliation":[]},{"given":"Nacim","family":"Belkhir","sequence":"additional","affiliation":[]},{"given":"Sinji","family":"Suzuki","sequence":"additional","affiliation":[]}],"member":"263","reference":[{"key":"ref10","doi-asserted-by":"publisher","DOI":"10.1016\/j.rcim.2010.06.017"},{"key":"ref11","first-page":"493","article-title":"Hierarchical recurrent neural networks for long-term dependencies","author":"el hihi","year":"1996","journal-title":"Advances in neural information processing systems"},{"journal-title":"Training Recurrent Neural Networks","year":"2013","author":"sutskever","key":"ref12"},{"key":"ref13","first-page":"1310","article-title":"On the difficulty of training recurrent neural networks","author":"pascanu","year":"2013","journal-title":"International Conference on Machine Learning"},{"key":"ref14","doi-asserted-by":"publisher","DOI":"10.1073\/pnas.79.8.2554"},{"key":"ref15","doi-asserted-by":"publisher","DOI":"10.1109\/72.279181"},{"key":"ref16","volume":"91","author":"hochreiter","year":"1991","journal-title":"Untersuchungen zu dynamischen neuronalen Netzen"},{"key":"ref17","volume":"abs 1609 4747","author":"ruder","year":"2016","journal-title":"An overview of gradient descent optimization algorithms"},{"key":"ref18","first-page":"26","article-title":"Lecture 6.5-rmsprop: Divide the gradient by a running average of its recent magnitude","volume":"4","author":"tieleman","year":"2012","journal-title":"COURSERA Neural Networks for Machine Learning"},{"journal-title":"Adam A method for stochastic optimization","year":"2014","author":"kingma","key":"ref19"},{"key":"ref4","doi-asserted-by":"publisher","DOI":"10.1016\/j.arcontrol.2008.03.008"},{"key":"ref3","doi-asserted-by":"publisher","DOI":"10.1016\/0005-1098(92)90053-I"},{"key":"ref6","doi-asserted-by":"publisher","DOI":"10.1162\/neco.1997.9.8.1735"},{"journal-title":"Fault Tolerant Flight Control via Adaptive Neural Network Augmentation","year":"1998","author":"rysdyk","key":"ref5"},{"key":"ref8","doi-asserted-by":"publisher","DOI":"10.2514\/6.2005-5886"},{"key":"ref7","doi-asserted-by":"publisher","DOI":"10.2514\/1.52400"},{"key":"ref2","first-page":"1073","article-title":"Neural networks based system identification techniques for model based fault detection of nonlinear systems","volume":"3","author":"fekih","year":"2007","journal-title":"International Journal of Innovative Computing Information and Control"},{"key":"ref9","doi-asserted-by":"publisher","DOI":"10.1006\/mssp.2001.1462"},{"journal-title":"Annual growth in global air traffic passenger demand from 2005 to 2017","year":"2017","key":"ref1"},{"key":"ref20","first-page":"2121","article-title":"Adaptive subgradient methods for online learning and stochastic optimization","volume":"12","author":"duchi","year":"2011","journal-title":"Journal of Machine Learning Research"},{"key":"ref22","doi-asserted-by":"publisher","DOI":"10.1109\/37.126844"},{"journal-title":"Incorporating nesterov momentum into adam","year":"2016","author":"dozat","key":"ref21"},{"key":"ref24","doi-asserted-by":"publisher","DOI":"10.1109\/MCS.2012.2214134"},{"key":"ref23","doi-asserted-by":"publisher","DOI":"10.1109\/MCAS.2009.933854"},{"key":"ref25","volume":"17","author":"lewis","year":"2013","journal-title":"Reinforcement Learning and Approximate Dynamic Programming for Feedback Control"}],"event":{"name":"2017 11th Asian Control Conference (ASCC)","start":{"date-parts":[[2017,12,17]]},"location":"Gold Coast, QLD","end":{"date-parts":[[2017,12,20]]}},"container-title":["2017 11th Asian Control Conference (ASCC)"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx7\/8267339\/8287090\/08287391.pdf?arnumber=8287391","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2018,3,16]],"date-time":"2018-03-16T15:48:41Z","timestamp":1521215321000},"score":1,"resource":{"primary":{"URL":"http:\/\/ieeexplore.ieee.org\/document\/8287391\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2017,12]]},"references-count":25,"URL":"https:\/\/doi.org\/10.1109\/ascc.2017.8287391","relation":{},"subject":[],"published":{"date-parts":[[2017,12]]}}}