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Stochastic higher-order three-scale strength prediction model for composite structures with micromechanical analysis 期刊论文
JOURNAL OF COMPUTATIONAL PHYSICS, 2022, 卷号: 465, 页码: 30
作者:  Dong, Hao;  Yang, Zihao;  Guan, Xiaofei;  Cui, Junzhi
收藏  |  浏览/下载：78/0  |  提交时间：2023/02/07
Composite structures  Multiscale random configurations  SHTSP model  Multilevel strategy  Strength prediction  
Delay-Compound-Compensation Control for Photoelectric Tracking System Based on Improved Smith Predictor Scheme 期刊论文
IEEE PHOTONICS JOURNAL, 2022, 卷号: 14, 期号: 3, 页码: 8
作者:  Luo, Yong;  Xue, Wenchao;  He, Wei;  Nie, Kang;  Mao, Yao;  Guerrero, Josep M.
收藏  |  浏览/下载：112/0  |  提交时间：2022/06/21
Delays  Trajectory  Feedforward systems  Bandwidth  Target tracking  Predictive models  Performance evaluation  Smith predictor  time delay  charge-couple device  delay-compound-compensation  trajectory prediction  velocity feedforward  
Conformalized temporal convolutional quantile regression networks for wind power interval forecasting 期刊论文
ENERGY, 2022, 卷号: 248, 页码: 16
作者:  Hu, Jianming;  Luo, Qingxi;  Tang, Jingwei;  Heng, Jiani;  Deng, Yuwen
收藏  |  浏览/下载：55/0  |  提交时间：2023/02/07
Wind power interval prediction  Temporal convolutional network  Conformalized quantile regression  
Cross-Network Skip-Gram Embedding for Joint Network Alignment and Link Prediction 期刊论文
IEEE TRANSACTIONS ON KNOWLEDGE AND DATA ENGINEERING, 2022, 卷号: 34, 期号: 3, 页码: 1080-1095
作者:  Du, Xingbo;  Yan, Junchi;  Zhang, Rui;  Zha, Hongyuan
收藏  |  浏览/下载：122/0  |  提交时间：2022/04/02
Task analysis  Predictive models  Social network services  Peer-to-peer computing  Optimization  Computational modeling  Computer science  Link prediction  network alignment  cross-network embedding  skip-gram  biased random walk  
Big Data in Forecasting Research: A Literature Review 期刊论文
BIG DATA RESEARCH, 2022, 卷号: 27, 页码: 30
作者:  Tang, Ling;  Li, Jieyi;  Du, Hongchuan;  Li, Ling;  Wu, Jun;  Wang, Shouyang
收藏  |  浏览/下载：136/0  |  提交时间：2022/04/02
Big data  Forecasting  Literature review  Prediction models  Information