A Model of Electronic Document Management of Technical Documentation for Railway Automation

Baratov, Dilshod; Aripov, Nazirjon; Muhiddinov, Obidjon; Jumanov, X.

doi:10.1007/978-3-030-85057-9_40

Cited by 2 publications

(1 citation statement)

References 23 publications

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“…The route setting based on the artificial neural network model [19][20][21][22][23][24][25][26][27][28][29][30][31][32][33][34][35] is shown in Figure 1, accounting for the train's moving stations. We will construct the neuron set in two layers in this instance [34][35].…”

Section: Methodsmentioning

confidence: 99%

Development of a route setting model in the dispatching centralization system

Mukhiddinov,

Boltayev,

Yunusova

et al. 2024

E3S Web Conf.

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These days, automation and remote control technologies provide the foundation for the organization of train movement across several categories. At railroad sections and stations, dispatcher centralization systems are utilized to guarantee the security of train movement. However, in the railroad portions where high-speed train movements are organized, time limitations based on the human factor are being implemented. Consequently, this results in longer wait times for technological processes at stations and longer train intervals on some railway segments. Developing an automated route preparation procedure at stations in dispatching centralization systems will allow for the resolution of current issues. A dispatching centralized system model for route establishment has been created in this scientific study. Using a two-layer neural network, a mathematical model of route setting in the dispatcher centralization system was determined. Neural networks are employed in rail dispatch rooms for intelligent route comparison and in dispatcher centralized systems for tracking train routes at stations.

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