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GraphCA: Learning From Graph Counterfactual Augmentation for Knowledge Tracing 期刊论文
IEEE/CAA Journal of Automatica Sinica, 2023, 卷号: 10, 期号: 11, 页码: 2108-2123
作者:  Xinhua Wang;  Shasha Zhao;  Lei Guo;  Lei Zhu;  Chaoran Cui;  Liancheng Xu
Adobe PDF(1627Kb)  |  收藏  |  浏览/下载：133/53  |  提交时间：2023/09/22
Contrastive learning  counterfactual representation  graph neural network  knowledge tracing  
A Data-Driven Rutting Depth Short-Time Prediction Model With Metaheuristic Optimization for Asphalt Pavements Based on RIOHTrack 期刊论文
IEEE/CAA Journal of Automatica Sinica, 2023, 卷号: 10, 期号: 10, 页码: 1918-1932
作者:  Zhuoxuan Li;  Iakov Korovin;  Xinli Shi;  Sergey Gorbachev;  Nadezhda Gorbacheva;  Wei Huang;  Jinde Cao
Adobe PDF(3879Kb)  |  收藏  |  浏览/下载：138/50  |  提交时间：2023/09/07
Extreme learning machine algorithm with residual correction (RELM), metaheuristic optimization  oil-gas transportation  RIOHTrack  rutting depth  
Human-Like Decision-Making of Autonomous Vehicles in Dynamic Traffic Scenarios 期刊论文
IEEE/CAA Journal of Automatica Sinica, 2023, 卷号: 10, 期号: 10, 页码: 1905-1917
作者:  Tangyike Zhang;  Junxiang Zhan;  Jiamin Shi;  Jingmin Xin;  Nanning Zheng
Adobe PDF(2815Kb)  |  收藏  |  浏览/下载：188/69  |  提交时间：2023/09/07
Autonomous vehicles  decision-making  driving behavior  human-like driving  
Competitive Meta-Learning 期刊论文
IEEE/CAA Journal of Automatica Sinica, 2023, 卷号: 10, 期号: 9, 页码: 1902-1904
作者:  Boxi Weng;  Jian Sun;  Gao Huang;  Fang Deng;  Gang Wang;  Jie Chen
Adobe PDF(608Kb)  |  收藏  |  浏览/下载：168/68  |  提交时间：2023/08/10
Steps Toward Industry 5.0: Building “6S” Parallel Industries With Cyber-Physical-Social Intelligence 期刊论文
IEEE/CAA Journal of Automatica Sinica, 2023, 卷号: 10, 期号: 8, 页码: 1692-1703
作者:  Xingxia Wang;  Jing Yang;  Yutong Wang;  Qinghai Miao;  Fei-Yue Wang;  Aijun Zhao;  Jian-Ling Deng;  Lingxi Li;  Xiaoxiang Na;  Ljubo Vlacic
Adobe PDF(15811Kb)  |  收藏  |  浏览/下载：154/31  |  提交时间：2023/07/20
ACP  artificial intelligence  CPS  CPSS  Industry 4.0  Industry 5.0  parallel industries  parallel intelligence  
Tensor Distribution Regression Based on the 3D Conventional Neural Networks 期刊论文
IEEE/CAA Journal of Automatica Sinica, 2023, 卷号: 10, 期号: 7, 页码: 1628-1630
作者:  Lin Chen;  Xin Luo
Adobe PDF(769Kb)  |  收藏  |  浏览/下载：72/30  |  提交时间：2023/06/14
Local-to-Global Causal Reasoning for Cross-Document Relation Extraction 期刊论文
IEEE/CAA Journal of Automatica Sinica, 2023, 卷号: 10, 期号: 7, 页码: 1608-1621
作者:  Haoran Wu;  Xiuyi Chen;  Zefa Hu;  Jing Shi;  Shuang Xu;  Bo Xu
Adobe PDF(2465Kb)  |  收藏  |  浏览/下载：156/50  |  提交时间：2023/06/14
Causal reasoning  cross document  graph reasoning  relation extraction (RE)  
Pavement Cracks Coupled With Shadows: A New Shadow-Crack Dataset and A Shadow-Removal-Oriented Crack Detection Approach 期刊论文
IEEE/CAA Journal of Automatica Sinica, 2023, 卷号: 10, 期号: 7, 页码: 1593-1607
作者:  Lili Fan;  Shen Li;  Ying Li;  Bai Li;  Dongpu Cao;  Fei-Yue Wang
Adobe PDF(23502Kb)  |  收藏  |  浏览/下载：125/16  |  提交时间：2023/06/14
Automatic pavement crack detection  data augmentation compensation  deep learning  residual feature augmentation  shadow removal  shadow-crack dataset  
Estimating the State of Health for Lithium-ion Batteries: A Particle Swarm Optimization-Assisted Deep Domain Adaptation Approach 期刊论文
IEEE/CAA Journal of Automatica Sinica, 2023, 卷号: 10, 期号: 7, 页码: 1530-1543
作者:  Guijun Ma;  Zidong Wang;  Weibo Liu;  Jingzhong Fang;  Yong Zhang;  Han Ding;  Ye Yuan
Adobe PDF(4250Kb)  |  收藏  |  浏览/下载：171/70  |  提交时间：2023/06/14
Deep transfer learning  domain adaptation  hyperparameter selection  lithium-ion batteries (LIBs)  particle swarm optimization  state of health estimation (SOH)  
Proximal Alternating-Direction-Method-of- Multipliers-Incorporated Nonnegative Latent Factor Analysis 期刊论文
IEEE/CAA Journal of Automatica Sinica, 2023, 卷号: 10, 期号: 6, 页码: 1388-1406
作者:  Fanghui Bi;  Xin Luo;  Bo Shen;  Hongli Dong;  Zidong Wang
Adobe PDF(2741Kb)  |  收藏  |  浏览/下载：166/61  |  提交时间：2023/05/29
Data science  high-dimensional and incomplete data  knowledge acquisition  industrial application  nonnegative latent factor analysis (NLFA)  proximal alternating direction method of multipliers  representation learning