JIPS (한국정보처리학회)
Current Result Document :
| 한글제목(Korean Title) |
Layout Optimization Method of Railway Transportation Route Based on Deep Convolution Neural Network |
| 영문제목(English Title) |
Layout Optimization Method of Railway Transportation Route Based on Deep Convolution Neural Network |
| 저자(Author) |
Cong Qiao
Qifeng Gao
Huayan Xing
|
| 원문수록처(Citation) |
VOL 19 NO. 01 PP. 0046 ~ 0054 (2023. 02) |
한글내용
(Korean Abstract) |
|
영문내용
(English Abstract) |
To improve the railway transportation capacity and maximize the benefits of railway transportation, a method for layout optimization of railway transportation route based on deep convolution neural network is proposed in this study. Considering the transportation cost of railway transportation and other factors, the layout model of railway transportation route is constructed. Based on improved ant colony algorithm, the layout model of railway transportation route was optimized, and multiple candidate railway transportation routes were output. Taking into account external information such as regional information, weather conditions and actual information of railway transportation routes, optimization of the candidate railway transportation routes obtained by the improved ant colony algorithm was performed based on deep convolution neural network, and the optimal railway transportation routes were output, and finally layout optimization of railway transportation routes was realized. The experimental results show that the proposed method can obtain the optimal railway transportation route, the shortest transportation length, and the least transportation time, maximizing the interests of railway transportation enterprises. |
| 키워드(Keyword) |
Ant Colony
Convolutional Neural Network
Layout Optimization
Railway
Transportation
Transportation Route
|
| 파일첨부 |
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