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학술연구/단체지원/교육 등 연구자 활동을 지속하도록 DBpia가 지원하고 있어요.
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논문 기본 정보
- 자료유형
- 학술저널
- 저자정보
- 저널정보
- 국제구조공학회 Smart Structures and Systems, An International Journal Smart Structures and Systems, An International Journal Vol.27 No.2
- 발행연도
- 2021.1
- 수록면
- 241 - 256 (16page)
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초록· 키워드
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In bridge weigh-in-motion (BWIM), dynamic bridge response is measured during traffic and used to identify overloaded vehicles. Most past studies of BWIM use mechanics-based algorithms to estimate axle weights. This research instead investigates deep learning, specifically the recurrent neural network (RNN), toward BWIM. In order to acquire the large data volume to train a RNN network that uses bridge response to estimate axle weights, a finite element bridge model is built through the commercial software package LS-DYNA. To mimic everyday traffic scenarios, tens of thousands of randomized vehicle formations are simulated, with different combinations of vehicle types, spacings, speeds, axle weights, axle distances, etc. Dynamic response from each of the randomized traffic scenarios is recorded for training the RNN. In this paper we propose a 3-stage Bidirectional RNN toward BWIM. Long short-term memory (LSTM) and attention mechanism are embedded in the BRNN to further improve the network performance. Additional test data indicates that the BRNN network achieves high accuracy in estimating axle weights, in comparison with a conventional moving force identification (MFI) method.
목차
등록된 정보가 없습니다.
참고문헌 (40)
참고문헌 신청
T.H.T. Chan / 1999 / AN INTERPRETIVE METHOD FOR MOVING FORCE IDENTIFICATION / Journal of Sound and Vibration 219(3):503~524
Cho, K. / 2014 / On the properties of neural machine translation : encoderdecoder approaches / Proceedings of SSST-8, Eighth Workshop on Syntax, Semantics and Structure in Statistical Translation
Chorowski, J. / 2014 / End-to-end continuous speech recognition using attentionbased recurrent NN : first results / Deep Learning and Representation Learning Workshop: NIPS 2014
Chung, J. / 2014 / Empirical evaluation of gated recurrent neural networks on sequence modeling / Deep Learning and Representation Learning Workshop : NIPS 2014
Das, P. / 2016 / History and Evolution of GPU Architecture / IGI Global
Cho, K. / 2014 / On the properties of neural machine translation : encoderdecoder approaches / Proceedings of SSST-8, Eighth Workshop on Syntax, Semantics and Structure in Statistical Translation
Chorowski, J. / 2014 / End-to-end continuous speech recognition using attentionbased recurrent NN : first results / Deep Learning and Representation Learning Workshop: NIPS 2014
Chung, J. / 2014 / Empirical evaluation of gated recurrent neural networks on sequence modeling / Deep Learning and Representation Learning Workshop : NIPS 2014
Das, P. / 2016 / History and Evolution of GPU Architecture / IGI Global
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