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| energy consumption optimization for high-speed railway based on particle swarm algorithm | |
| Sun Shiyao; Li Yang; Xu Huaiyu | |
| 2012 | |
| Conference Name | 4th International Conference on Computational Intelligence and Communication Networks, CICN 2012 |
| Source | Proceedings - 4th International Conference on Computational Intelligence and Communication Networks, CICN 2012 |
| Pages | 879-882 |
| Conference Date | November 3, 2012 - November 5, 2012 |
| Conference Place | Mathura, Uttar Pradesh, India |
| Indexed Type | EI |
| Department | (1) Integrated Circuit Applied Software Lab. Software College Northeastern University Shenyang China; (2) Service Science Research Center Shanghai Advanced Research Institute Chinese Academy of Sciences China |
| English Abstract | From the point of the perspective of train control strategies, energy saving for high-speed railway will be explored in this paper. The energy consumption of high-speed railway is mainly used for train operation, accounting for about 87%. This paper definitely presents a particle swarm algorithm to compute the energy consumption, which aims to reduce the railway energy by obtaining optimal train control strategies. The algorithm establishes a fresh mathematical model, setting energy consumption, running time and stop accuracy as objects, setting limited velocity and motion as constraint condition, and develops an improved adaptive novel multi-population particle swarm with novel crossover and mutation strategies, in order to reduce the computational complexity and ensure the accuracy of the energy consumption results. Over all, a simulation system has been built to resolute problems of high-speed railway. According to the simulation results, the algorithm is proved to be efficient and helpful on energy saving. © 2012 IEEE.; From the point of the perspective of train control strategies, energy saving for high-speed railway will be explored in this paper. The energy consumption of high-speed railway is mainly used for train operation, accounting for about 87%. This paper definitely presents a particle swarm algorithm to compute the energy consumption, which aims to reduce the railway energy by obtaining optimal train control strategies. The algorithm establishes a fresh mathematical model, setting energy consumption, running time and stop accuracy as objects, setting limited velocity and motion as constraint condition, and develops an improved adaptive novel multi-population particle swarm with novel crossover and mutation strategies, in order to reduce the computational complexity and ensure the accuracy of the energy consumption results. Over all, a simulation system has been built to resolute problems of high-speed railway. According to the simulation results, the algorithm is proved to be efficient and helpful on energy saving. © 2012 IEEE. |
| Keyword | Algorithms Artificial Intelligence Energy Conservation Energy Utilization Mathematical Models Optimization Railroad Plant And Structures |
| Language | 英语 |
| Content Type | 会议论文 |
| URI | http://ir.iscas.ac.cn/handle/311060/15968 |
| Collection | 中国科学院软件研究所 |
| Recommended Citation GB/T 7714 | Sun Shiyao,Li Yang,Xu Huaiyu. energy consumption optimization for high-speed railway based on particle swarm algorithm[C],2012:879-882. |
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