A Real-Time Train Timetable Rescheduling Method Based on Deep Learning for Metro Systems Energy Optimization under Random Disturbances
Considering that uncertain dwell disturbances often occur at metro stations, researchers have proposed many methods for solving the train timetable rescheduling (TTR) problem. This paper proposes a Modified Genetic Algorithm-Gate Recurrent Unit (MGA-GRU) method, which is a real-time TTR method based...
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Main Authors: | Jinlin Liao, Feng Zhang, Shiwen Zhang, Cheng Gong |
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Format: | Article |
Language: | English |
Published: |
Wiley
2020-01-01
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Series: | Journal of Advanced Transportation |
Online Access: | http://dx.doi.org/10.1155/2020/8882554 |
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