Algorithm of Energy Efficiency Improvement for Intelligent Devices in Railway Transport

IF 0.5 Q4 ENGINEERING, ELECTRICAL & ELECTRONIC Electrical Control and Communication Engineering Pub Date : 2016-07-01 DOI:10.1515/ecce-2016-0004
A. Beinarovica, M. Gorobecs, Anatolijs Ļevčenkovs
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引用次数: 1

Abstract

Abstract The present paper deals with the use of systems and devices with artificial intelligence in the motor vehicle driving. The main objective of transport operations is a transportation planning with minimum energy consumption. There are various methods for energy saving, and the paper discusses one of them – proper planning of transport operations. To gain proper planning it is necessary to involve the system and devices with artificial intelligence. They will display possible developments in the choice of one or another transport plan. Consequently, it can be supposed how much the plan is effective against the spent energy. The intelligent device considered in this paper consists of an algorithm, a database, and the internet for the connection to other intelligent devices. The main task of the target function is to minimize the total downtime at intermediate stations. A specific unique PHP-based computer model was created. It uses the MySQL database for simulation data storage and processing. Conclusions based on the experiments were made. The experiments showed that after optimization, a train can pass intermediate stations without making multiple stops breaking and accelerating, which leads to decreased energy consumption.
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铁路运输智能设备能效提升算法
摘要:本文讨论了人工智能系统和设备在机动车驾驶中的应用。运输作业的主要目标是以最小的能源消耗进行运输规划。节能的方法有很多种,本文讨论了其中的一种——合理规划运输作业。为了获得适当的规划,有必要将系统和设备与人工智能结合起来。他们将展示在选择一种或另一种运输方案时可能出现的发展。因此,可以假设该计划对消耗的能量有多大效果。本文所考虑的智能设备由算法、数据库和用于与其他智能设备连接的internet组成。目标函数的主要任务是最小化中间站的总停机时间。创建了一个特定的独特的基于php的计算机模型。采用MySQL数据库对仿真数据进行存储和处理。通过实验得出结论。实验结果表明,优化后的列车在通过中间站时,无需多次断行加速,从而降低了能耗。
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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来源期刊
Electrical Control and Communication Engineering
Electrical Control and Communication Engineering ENGINEERING, ELECTRICAL & ELECTRONIC-
自引率
14.30%
发文量
0
审稿时长
12 weeks
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