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Fine-Grained Trajectory-Based Travel Time Estimation for Multi-City Scenarios Based on Deep Meta-Learning 期刊论文
IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS, 2022, 页码: 13
作者:  Wang, Chenxing;  Zhao, Fang;  Zhang, Haichao;  Luo, Haiyong;  Qin, Yanjun;  Fang, Yuchen
收藏  |  浏览/下载：19/0  |  提交时间：2022/12/07
Estimation  Trajectory  Task analysis  Urban areas  Roads  Data models  Global Positioning System  Spatial-temporal data mining  travel time estimation  meta learning  deep learning  
Predicting the Noise Covariance With a Multitask Learning Model for Kalman Filter-Based GNSS/INS Integrated Navigation 期刊论文
IEEE TRANSACTIONS ON INSTRUMENTATION AND MEASUREMENT, 2021, 卷号: 70, 页码: 13
作者:  Wu, Fan;  Luo, Haiyong;  Jia, Hongwei;  Zhao, Fang;  Xiao, Yimin;  Gao, Xile
收藏  |  浏览/下载：36/0  |  提交时间：2021/12/01
Adaptive integrated navigation  deep learning  denoising autoencoder (DAE)  Kalman filter (KF)  measurement noise  process noise  
Heterogeneous Multi-Task Learning for Multiple Pseudo-Measurement Estimation to Bridge GPS Outages 期刊论文
IEEE TRANSACTIONS ON INSTRUMENTATION AND MEASUREMENT, 2021, 卷号: 70, 页码: 16
作者:  Lu, Shuangqiu;  Gong, Yilin;  Luo, Haiyong;  Zhao, Fang;  Li, Zhaohui;  Jiang, Jinguang
收藏  |  浏览/下载：30/0  |  提交时间：2021/12/01
Artificial intelligence (AI) and neural networks (NNs)  global position system (GPS) outages  inertial navigation system (INS)/GPS integrated navigation  multi-task learning (MTL)  multiple pseudo-measurement estimation  
ADST: Forecasting Metro Flow Using Attention-Based Deep Spatial-Temporal Networks with Multi-Task Learning 期刊论文
SENSORS, 2020, 卷号: 20, 期号: 16, 页码: 23
作者:  Jia, Hongwei;  Luo, Haiyong;  Wang, Hao;  Zhao, Fang;  Ke, Qixue;  Wu, Mingyao;  Zhao, Yunyun
收藏  |  浏览/下载：51/0  |  提交时间：2020/12/10
forecasting passenger flow  spatiotemporal networks  multi-task learning  attention mechanism  spatiotemporal dependency