The Procedure for Planning the Operation of Low-Intensity Railway Lines: Logistical Aspects and Neural Network Models

Abstract

Purpose: Improving the efficiency of the line functioning based on the development of a procedure for planning the operation of low-intensity railway lines based on neural networks. Methods: Methods of analysis, synthesis, machine learning, neural network modeling have been applied. Results: Using regression multiple analysis and mathematical tools, a set of neural network models for planning the operation of a low-intensity railway line according to a set of indicators has been developed. Planning parameters have been determined, which enable the railway line operations to achieve a positive financial outcome. Practical significance: The conducted research is an effective tool for improving the planning of the work of low-intensity railway lines.