基于案例推理的铁路货物装载与加固方案研究

Qingwei Kong, Nan Li, Xiaofang Feng, Weibin Liu
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引用次数: 0

摘要

铁路货物装载加固对运输安全起着至关重要的作用。中国的货运业务分布非常广泛,但很多货运站仍然采用手工绘图和计算的方式,根据工作人员的经验进行计算,导致实用性差,效率低。本文提出了一种基于案例推理(CBR)和可拓理论的方案生成方法。本研究将智能算法与铁路货物装载与加固理论知识相结合,可实现复杂装载场景下装载与加固方案的自动匹配与生成。通过算例验证了该方案的可靠性。该研究简化了荷载和配筋方案的生成过程。这对提高货运运行效率和发展智能控制技术具有重要意义。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Research on Railway Freight Loading and Reinforcement Schemes based on Case-based Reasoning, CBR
Railway freight loading and reinforcement plays an essential role in transportation security. China has an enormous spread of freight operation, however, a great number of freight stations still use manual drawing and calculation based on the staff's experience, which causes poor practicability and low efficiency. In this research, a method of generating schemes based on Case-based Reasoning (CBR) and extension theory was proposed. The study combines intelligent algorithms and theoretical knowledge in railway freight loading and reinforcement, which can implement auto-matching and generation of loading and reinforcement schemes under complex loading scenarios. The reliability of the scheme is also verified through an example. The research simplifies the generation process of loading and reinforcement scheme. It has a great significance in increasing freight operation efficiency and developing intelligent control technology.
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