备用邮箱
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工作邮箱：yuhang@shu.edu.cn
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portfolio
publications
Online Topology Learning by a Gaussian Membership-Based Self-Organizing Incremental Neural Network
Published in IEEE Transactions on Neural Networks and Learning Systems, 2019
JCR 1区，中科院1区，CCF B，影响因子：10.451
Recommended citation: Yu H, Lu J, Zhang G. Online topology learning by a gaussian membership-based self-organizing incremental neural network[J]. IEEE transactions on neural networks and learning systems, 2019, 31(10): 3947-3961. https://ieeexplore.ieee.org/document/8897716
An Online Robust Support Vector Regression for Data Streams
Published in IEEE Transactions on Knowledge and Data Engineering, 2020
JCR 1区，中科院2区，CCF A类，影响因子：6.977
Recommended citation: Yu H, Lu J, Zhang G. An online robust support vector regression for data streams[J]. IEEE Transactions on Knowledge and Data Engineering, 2020, 34(1): 150-163. https://ieeexplore.ieee.org/document/9034023
Continuous Support Vector Regression for Nonstationary Streaming Data
Published in IEEE Transactions on Cybernetics, 2020
JCR 1区，中科院1区，CCF B，影响因子：10.451
Recommended citation: Yu H, Lu J, Zhang G. Continuous support vector regression for nonstationary streaming data[J]. IEEE transactions on cybernetics, Early Access, 2020. https://ieeexplore.ieee.org/document/9194301
Topology Learning-based Fuzzy Random Neural Network for Streaming Data Regression
Published in IEEE Transactions on Fuzzy Systems, 2020
JCR 1区，中科院1区，CCF B类，影响因子：12.029.
Recommended citation: Yu H, Lu J, Zhang G. Topology learning-based fuzzy random neural network for streaming data regression[J]. IEEE Transactions on Fuzzy Systems, 2020. https://ieeexplore.ieee.org/document/9265257
MORStreaming: A Multioutput Regression System for Streaming Data
Published in IEEE Transactions on Systems, Man, and Cybernetics: Systems, 2021
JCR 1区，中科院1区，影响因子：12.029.
Recommended citation: Yu H, Lu J, Zhang G. MORStreaming: A Multioutput Regression System for Streaming Data[J]. IEEE Transactions on Systems, Man, and Cybernetics: Systems, Early Access, 2021. https://ieeexplore.ieee.org/document/9526914
Real-Time Prediction System of Train Carriage Load Based on Multi-Stream Fuzzy Learning
Published in IEEE Transactions on Intelligent Transportation Systems, 2022
JCR 1区，中科院2区，CCF B类，影响因子：6.492
Recommended citation: Yu H, Lu J, Liu A, et al. Real-Time Prediction System of Train Carriage Load Based on Multi-Stream Fuzzy Learning[J]. IEEE Transactions on Intelligent Transportation Systems, Early Access，2022. https://ieeexplore.ieee.org/document/9678130
talks
Talk 1 on Relevant Topic in Your Field
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This is a description of your talk, which is a markdown files that can be all markdown-ified like any other post. Yay markdown!
Conference Proceeding talk 3 on Relevant Topic in Your Field
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This is a description of your conference proceedings talk, note the different field in type. You can put anything in this field.
teaching
刘炜旭
研究生, 攻读博士, 2021
2021级研究生
张青勇
研究生, 花旗银行, 算法工程师, 2021
2021级研究生
孙一平
研究生, 锐嘉科集团有限公司, JAVA工程师, 2021
2021级研究生
金澄
研究生, 交通银行，算法工程师, 2021
2021级研究生
马秋波
研究生, 京东集团，后端工程师, 2022
2022级研究生
周小杰
研究生, 上海张江数学研究院，算法工程师, 2022
2022级研究生
郑海霆
研究生, 中国电气装备集团科学技术研究院，人工智能算法工程师, 2022
2022级研究生
李瑞林
研究生, 攻读博士-多伦多大学, 2022
2022级研究生
余延森
研究生, 攻读博士-上海大学, 2022
2022级研究生