低强度铁路运营规划程序:后勤方面和神经网络模型

Konstantin Kovalev, A. Novichihin
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引用次数: 0

摘要

目的:基于开发基于神经网络的低强度铁路线路运营规划程序,提高线路运行效率。方法:运用分析、综合、机器学习、神经网络建模等方法。结果:利用回归多元分析和数学工具,建立了一套基于指标集的低强度铁路线路运营规划神经网络模型。规划参数已经确定,这使铁路线的运营取得了积极的财务成果。现实意义:本研究为改进低强度铁路线路的规划工作提供了有效的工具。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
The Procedure for Planning the Operation of Low-Intensity Railway Lines: Logistical Aspects and Neural Network Models
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.
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