A prediction model for complex equipment remaining useful life using gated recurrent unit complex networks-Reference-Cited by-同舟云学术

登录注册会员服务联系我们

A prediction model for complex equipment remaining useful life using gated recurrent unit complex networks

Published:2021-11-30 Issue: Volume: Page:1-17
ISSN:1751-7575
Container-title:Enterprise Information Systems
language:en
Short-container-title:Enterprise Information Systems

Author:

Tong Sheng¹,Yang Jie²,Zong Haohua³

Affiliation:

1. Air Traffic Control and Navigation School, Air Force Engineering University, Xi’an, China

2. WaveCoRE Research Group, Catholic University of Leuven, Leuven, Belgium

3. Aerospace Engineering Faculty, Technische Universiteit Delft, Delft, Netherlands

Publisher

Informa UK Limited

Subject

Information Systems and Management,Computer Science Applications

Link

https://www.tandfonline.com/doi/pdf/10.1080/17517575.2021.2008515

Reference33 articles.

1. Fault tolerance through automatic cell isolation using three-dimensional cellular genetic algorithms

2. Deep Convolutional Neural Network Based Regression Approach for Estimation of Remaining Useful Life

3. Gated recurrent unit based recurrent neural network for remaining useful life prediction of nonlinear deterioration process

4. Advanced manufacturing systems: supply–demand matching of manufacturing resource based on complex networks and Internet of Things

Cited by 3 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Remaining Useful Life Prediction of High-Speed Railroad Contact Network Based on Stacking Integrated Attention-LSTM-CNN Deep Learning;Arabian Journal for Science and Engineering;2024-03-12

2. A Model Based on CNN-LSTM for the Remaining Life Prediction of Equipment in Aircraft Assembly Pulsation Production Line;Journal of Physics: Conference Series;2024-01-01

3. Complex system health condition estimation using tree-structured simple recurrent unit networks;Complex & Intelligent Systems;2022-05-10

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线，采集、加工和组织学术论文而形成的新型学术文献查询和分析系统，可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容，当前同舟云学术共收录了国内外主流学术期刊6万余种，收集的期刊论文及会议论文总量共计约1.5亿篇，并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询！咨询电话：010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号京ICP备18003416号-3