A deep learning-assisted mathematical model for decongestion time prediction at railroad grade crossings (Oct, 10.1007/s00521-021-06625-z, 2021)

被引:0
|
作者
Jiang, Zhuocheng [1 ]
Guo, Feng [2 ]
Qian, Yu [2 ]
Wang, Yi [1 ]
Pan, W. David [3 ]
机构
[1] Univ South Carolina, Dept Mech Engn, Columbina, SC 29208 USA
[2] Univ South Carolina, Dept Civil & Environm Engn, Columbina, SC 29208 USA
[3] Univ Alabama, Dept Elect & Comp Engn, Huntsville, AL 35899 USA
来源
NEURAL COMPUTING & APPLICATIONS | 2022年 / 34卷 / 08期
关键词
D O I
10.1007/s00521-021-06767-0
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
引用
收藏
页码:6577 / 6577
页数:1
相关论文
共 3 条
  • [1] A deep learning-assisted mathematical model for decongestion time prediction at railroad grade crossings
    Jiang, Zhuocheng
    Guo, Feng
    Qian, Yu
    Wang, Yi
    Pan, W. David
    NEURAL COMPUTING & APPLICATIONS, 2022, 34 (06): : 4715 - 4732
  • [2] A deep learning-assisted mathematical model for decongestion time prediction at railroad grade crossings
    Zhuocheng Jiang
    Feng Guo
    Yu Qian
    Yi Wang
    W. David Pan
    Neural Computing and Applications, 2022, 34 : 4715 - 4732
  • [3] Correction to: A deep learning-assisted mathematical model for decongestion time prediction at railroad grade crossings
    Zhuocheng Jiang
    Feng Guo
    Yu Qian
    Yi Wang
    W. David Pan
    Neural Computing and Applications, 2022, 34 : 6577 - 6577