Abstract
The continuous expansion of rail transit lines has led to a significant increase in energy consumption. Choosing an appropriate timetable based on external conditions of train operation can reduce energy consumption by more than 5%. When emergencies occur in rail transit, external conditions change, rendering the original timetable unable to meet energy-saving requirements. This paper primarily explores how to quickly determine an energy-efficient timetable based on historical energy-saving timetable data and current external conditions using case-based reasoning methods. The paper represents emergency event timetable cases using a framework approach, and then employs a retrieval algorithm based on the grey correlation degree method to search for cases. The energy-efficient timetable for the target case is selected from the retrieved source cases, considering the one with the lowest energy consumption.
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.