Research and Development of an Intelligent System For Rapid Train Schedule Adjustment Based on Step-by-Step Neural Control

I. Makarov, R. Gorbachev, A. Novikov, E. Zakharova
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引用次数: 1

Abstract

This paper describes the realising and analysis of the applicability of artificial intelligence technology and game theory to resolve conflict situations that occur during railway traffic. In this technology, decision-making on the train traffic control on the railway section is based on the using of an intelligent management approach. The proposed approach includes a model of dispatcher operating in conflict situations and a model of railway traffic. The dispatcher operating model is implemented using a fully connected artificial neural network with several hidden layers. The neural network is trained using a genetic algorithm. The main idea of this approach is to approximate the problem of train traffic control to one of the problems of game theory, which involves a single player-dispatcher interacting with a group of agents-trains in a dynamic environment.
基于分步神经控制的列车快速调度智能系统的研究与开发
本文描述了人工智能技术和博弈论在解决铁路交通冲突情况中的适用性的实现和分析。在该技术中,采用智能管理方法对铁路路段的列车交通控制进行决策。所提出的方法包括一个在冲突情况下操作的调度员模型和一个铁路交通模型。调度器运行模型采用全连接人工神经网络实现,该网络具有多个隐藏层。神经网络使用遗传算法进行训练。该方法的主要思想是将列车交通控制问题近似为博弈论的问题之一,博弈论涉及单个玩家-调度员与动态环境中一组代理-列车的交互。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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