Zobrazeno 1 - 6
of 6
pro vyhledávání: '"Yuan‐wen Lai"'
Publikováno v:
IET Intelligent Transport Systems, Vol 17, Iss 4, Pp 716-729 (2023)
Abstract Accurate and stable short‐term passenger flow prediction is an indispensable part of current intelligent transportation systems. This paper proposes two deep learning prediction models based on convolutional neural networks (CNN) and long
Externí odkaz:
https://doaj.org/article/0d93267ae0c3402f9856350d671c49c3
Autor:
Yuan‐wen Lai, Yang Wang
Publikováno v:
IET Intelligent Transport Systems, Vol 17, Iss 4, Pp 825-834 (2023)
Abstract The subjectivity of selecting training parameters is an important factor affecting the accuracy of short‐term passenger flow prediction of rail transit by long short‐term memory (LSTM) neural network. In order to improve the prediction a
Externí odkaz:
https://doaj.org/article/dfbada61e36a4c5982db07d316b1260e
Autor:
Yuan‐wen Lai, Yang Wang
Publikováno v:
IET Intelligent Transport Systems. 17:825-834
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::af99a31acb691e3207ed880a4290fa4a
https://doi.org/10.1049/itr2.12306
https://doi.org/10.1049/itr2.12306
Publikováno v:
IET Intelligent Transport Systems. 17:716-729
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::03b409a6236afb0d9d61c99b6e6bd8ce
https://doi.org/10.1049/itr2.12298
https://doi.org/10.1049/itr2.12298
Publikováno v:
ICCTP 2011.
Pedestrians have a significant effect on capacity of signalized intersections with channelization island. This paper analyzes the regular arrival pattern of pedestrians and shows that the arrival frequency of pedestrians is consistent with negative b
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::e104a00229e7e14ea5526ed1316854af
https://doi.org/10.1061/41186(421)83
https://doi.org/10.1061/41186(421)83
Publikováno v:
ICCTP 2011; 2011, p848-858, 11p