Research on Railway Freight Loading and Reinforcement Schemes based on Case-based Reasoning, CBR
| Autor: | Xiaofang Feng, Weibin Liu, Nan Li, Qingwei Kong |
|---|---|
| Rok vydání: | 2020 |
| Předmět: |
Generation process
Intelligent algorithms Scheme (programming language) Transportation security Computer science Reliability (computer networking) ComputerApplications_COMPUTERSINOTHERSYSTEMS Case-based reasoning Reinforcement Intelligent control Industrial engineering computer computer.programming_language |
| Zdroj: | 2020 2nd International Conference on Industrial Artificial Intelligence (IAI). |
| DOI: | 10.1109/iai50351.2020.9262156 |
| Popis: | 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. |
| Databáze: | OpenAIRE |
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