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Title:
energy consumption optimization for high-speed railway based on particle swarm algorithm
Author: Sun Shiyao ; Li Yang ; Xu Huaiyu
Source: Proceedings - 4th International Conference on Computational Intelligence and Communication Networks, CICN 2012
Conference Name: 4th International Conference on Computational Intelligence and Communication Networks, CICN 2012
Conference Date: November 3, 2012 - November 5, 2012
Issued Date: 2012
Conference Place: Mathura, Uttar Pradesh, India
Keyword: Algorithms ; Artificial intelligence ; Energy conservation ; Energy utilization ; Mathematical models ; Optimization ; Railroad plant and structures
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
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.
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.
Language: 英语
Content Type: 会议论文
URI: http://ir.iscas.ac.cn/handle/311060/15968
Appears in Collections:软件所图书馆_会议论文

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Recommended Citation:
Sun Shiyao,Li Yang,Xu Huaiyu. energy consumption optimization for high-speed railway based on particle swarm algorithm[C]. 见:4th International Conference on Computational Intelligence and Communication Networks, CICN 2012. Mathura, Uttar Pradesh, India. November 3, 2012 - November 5, 2012.
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