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Accurate prediction of short-term photovoltaic power generation via a novel double-input-rule-modules stacked deep fuzzy method 期刊论文
ENERGY, 2020, 卷号: 212, 页码: 13
作者:  Li, Chengdong;  Zhou, Changgeng;  Peng, Wei;  Lv, Yisheng;  Luo, Xin
收藏  |  浏览/下载：220/0  |  提交时间：2021/03/08
PV power generation prediction  Deep fuzzy model  Double input rule module  Data driven method  Least square method  
Acting As A Decision Maker: Traffic-Condition-Aware Ensemble Learning for Traffic Flow Prediction 期刊论文
IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS, 2020, 期号: Accepted, 页码: Accepted
作者:  Yuanyuan Chen;  Hongyu Chen;  Peijun Ye;  Yisheng Lv;  Fei-Yue Wang
Adobe PDF(2382Kb)  |  收藏  |  浏览/下载：278/57  |  提交时间：2020/10/16
Traffic Flow Prediction  Ensemble Learning  Deep Learning  
Parallel Transportation Systems: Toward IoT-Enabled Smart Urban Traffic Control and Management 期刊论文
IEEE Transactions on Intelligent Transportation Systems, 2020, 卷号: 21, 期号: 10, 页码: 4063 - 4071
作者:  Fenghua Zhu;  Yisheng Lv;  Yuanyuan Chen;  Xiao Wang;  Gang Xiong;  Fei-Yue Wang
Adobe PDF(2879Kb)  |  收藏  |  浏览/下载：451/229  |  提交时间：2020/10/15
Intelligent transportation systems  
Taxi Demand Prediction Using Parallel Multi-Task Learning Model 期刊论文
IEEE Transactions on Intelligent Transportation Systems, 2020, 卷号: 99, 期号: 1, 页码: 1-10
作者:  Chizhan Zhang;  Fenghua Zhu;  Xiao Wang;  Leilei Sun;  Haina Tang;  Yisheng Lv
Adobe PDF(3947Kb)  |  收藏  |  浏览/下载：217/86  |  提交时间：2020/10/15
Taxi demand prediction, pick-up/drop-off demand, multi-task learning, LSTM, deep learning  
Traffic Flow Imputation Using Parallel Data and Generative Adversarial Networks 期刊论文
IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS, 2020, 卷号: 21, 期号: 4, 页码: 1624-1630
作者:  Chen, Yuanyuan;  Lv, Yisheng;  Wang, Fei-Yue
Adobe PDF(2070Kb)  |  收藏  |  浏览/下载：369/66  |  提交时间：2020/06/02
Generators  Data models  Gallium nitride  Generative adversarial networks  Training  Loss measurement  Biological system modeling  Parallel data  generative adversarial networks  traffic flow imputation  data augmentation  deep learning