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Deep graph level anomaly detection with contrastive learning 期刊论文
SCIENTIFIC REPORTS, 2022, 卷号: 12, 期号: 1, 页码: 11
作者:  Luo, Xuexiong;  Wu, Jia;  Yang, Jian;  Xue, Shan;  Peng, Hao;  Zhou, Chuan;  Chen, Hongyang;  Li, Zhao;  Sheng, Quan Z.
收藏  |  浏览/下载：69/0  |  提交时间：2023/02/07
Evaluation of a joint replenishment policy with sales-based threshold and stochastic demand 期刊论文
COMPUTERS & INDUSTRIAL ENGINEERING, 2022, 卷号: 172, 页码: 11
作者:  Wan, Guangyu;  Cao, Yu;  Wang, Shouyang
收藏  |  浏览/下载：58/0  |  提交时间：2023/02/07
Inventory control  Cost evaluation  Joint replenishment problem  Sales-based threshold  Semi-Markov chain  
A new PM2.5 concentration forecasting system based on AdaBoost-ensemble system with deep learning approach 期刊论文
JOURNAL OF FORECASTING, 2022, 页码: 22
作者:  Li, Zhongfei;  Gan, Kai;  Sun, Shaolong;  Wang, Shouyang
收藏  |  浏览/下载：66/0  |  提交时间：2023/02/07
AdaBoost-ensemble  deep learning  hybrid data preprocessing-analysis strategy  LSTM  
Asymptotic anatomy of the Berry phase for scalar waves in two-dimensional periodic continua 期刊论文
PROCEEDINGS OF THE ROYAL SOCIETY A-MATHEMATICAL PHYSICAL AND ENGINEERING SCIENCES, 2022, 卷号: 478, 期号: 2262, 页码: 28
作者:  Guzina, Bojan B.;  Oudghiri-Idrissi, Othman;  Meng, Shixu
收藏  |  浏览/下载：72/0  |  提交时间：2023/02/07
Berry phase  asymptotic model  scalar wave equation  Berry phase computation  
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：109/0  |  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  
A class of finite element methods with averaging techniques for solving the three-dimensional drift-diffusion model in semiconductor device simulations 期刊论文
JOURNAL OF COMPUTATIONAL PHYSICS, 2022, 卷号: 458, 页码: 24
作者:  Zhang, Qianru;  Wang, Qin;  Zhang, Linbo;  Lu, Benzhuo
收藏  |  浏览/下载：57/0  |  提交时间：2023/02/07
Three-dimensional drift -diffusion model  Averaging technique  Finite element method  Semiconductor device  
Model-Free Reinforcement Learning by Embedding an Auxiliary System for Optimal Control of Nonlinear Systems 期刊论文
IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS, 2022, 卷号: 33, 期号: 4, 页码: 1520-1534
作者:  Xu, Zhenhui;  Shen, Tielong;  Cheng, Daizhan
收藏  |  浏览/下载：86/0  |  提交时间：2022/06/21
Mathematical model  Trajectory  Heuristic algorithms  Optimal control  System dynamics  Artificial neural networks  Convergence  Approximate optimal control design  auxiliary trajectory  completely model-free  integral reinforcement learning (IRL)  
The GHG Emissions Assessment of Online Car-Hailing Development under the Intervention of Evaluation Policies in China 期刊论文
SUSTAINABILITY, 2022, 卷号: 14, 期号: 3, 页码: 25
作者:  Zeng, Isabella Yunfei;  Chen, Jingrui;  Niu, Ziheng;  Liu, Qingfei;  Wu, Tian
收藏  |  浏览/下载：128/0  |  提交时间：2022/04/02
online car-hailing services  GHG emissions assessment  emission reduction  regulation stringency  production and use stages  sustainable transportation  
Multi-step metal prices forecasting based on a data preprocessing method and an optimized extreme learning machine by marine predators algorithm 期刊论文
RESOURCES POLICY, 2021, 卷号: 74, 页码: 10
作者:  Du, Pei;  Guo, Ju'e;  Sun, Shaolong;  Wang, Shouyang;  Wu, Jing
收藏  |  浏览/下载：146/0  |  提交时间：2022/04/02
Metal prices forecasting  Data processing method  Optimized extreme learning machine  Hybrid forecasting model  
An innovative ensemble learning air pollution early-warning system for China based on incremental extreme learning machine 期刊论文
ATMOSPHERIC POLLUTION RESEARCH, 2021, 卷号: 12, 期号: 9, 页码: 15
作者:  Du, Zongjuan;  Heng, Jiani;  Niu, Mingfei;  Sun, Shaolong
收藏  |  浏览/下载：112/0  |  提交时间：2022/04/02
Air quality early-warning system  Length-changeable incremental extreme  learning machine  Hybrid ensemble model  Fuzzy evaluation