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Sresakoolchai, J. and Kaewunruen, S. (2023) Railway Infrastructure Maintenance Efficiency Improvement Using Deep Reinforcement Learning Integrated with Digital Twin Based on Track Geometry and Component Defects. Scientific Reports, 13, Article No. 2439.
https://doi.org/10.1038/s41598-023-29526-8

has been cited by the following article:

• TITLE: Functional Model of the E-Dispatcher Information System for Railway Automation and Telemechanics Maintenance Management

  AUTHORS: Shaxnoza Burxon qizi Otakulova, Nazirjon Mukarramovich Aripov

  KEYWORDS: E-Dispatcher, Telemechanics, Functional Model, Maintenance Database, Electronic Journal

  JOURNAL NAME: Intelligent Control and Automation, Vol.17 No.4, October 19, 2026

  ABSTRACT: This paper proposes a functional model of the E-dispatcher information system for integrated management of RAT maintenance processes. The system establishes information relationships between railway stations, RAT devices, maintenance plans, dispatcher tasks, responsible personnel, electronic journal records, archives, and audit trails within a unified information environment. A Boolean decision model for maintenance task release is formulated and minimized using the Karnaugh-map method, taking into account the maintenance task type, DSP/DNP operational permission, and authorization of the responsible employee.