A Novel Compression Algorithm for Spatiotemporal Data Based on PSO and GA
文献类型：会议论文
| 作者 | Wu JW(吴俊伟); Zhu YL(朱云龙) ; Ku T(库涛); Wang L(王亮)
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| 出版日期 | 2012 |
| 会议名称 | International Conference on Computational Intelligence and Software Engineering (CiSE 2012) |
| 会议日期 | December 14-16, 2012 |
| 会议地点 | Wuhan, China |
| 关键词 | Spatiotemporal Data compression genetic algorithm particle swarm optimization Douglas-Peucker algorithm |
| 页码 | 13-16 |
| 中文摘要 | Positioning applications have recently become extremely popular thanks to recent advances in telecommunications and geopositioning reporting devices (GPS, PDA etc.). It is thus to be expected that all these devices will start to generate an unprecedented stream of time-stamped positions leading to storage and computation challenges. Hence the need for trajectory compression arises. Previously most work has been done in compression mainly deal with two-dimensional spatial data without taking into account another important dimension: time. Besides, very few of the existing spatiotemporal compression algorithms, which cannot determine whether the final compression result is optimal, use optimization algorithms such as Genetic Algorithm (GA) and Particle Swam Optimation (PSO) algorithm. With these two points in mind, we propose a new trajectory compression algorithm based on the GA, PSO, and Douglas-Peucker algorithms to compress time-stamped position data. Experimental results illustrate that this compression method can archive large data compression ratio and high accuracy, and especially, can obtain the optimal or suboptimum compression result. |
| 产权排序 | 1 |
| 会议录 | International Conference on Computational Intelligence and Software Engineering (CiSE 2012)
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| 会议录出版者 | Scientific Research Publishing |
| 会议录出版地 | USA |
| 语种 | 英语 |
| ISBN号 | 978-1-61896-036-8 |
| 源URL | [http://ir.sia.cn/handle/173321/13824]  |
| 专题 | 沈阳自动化研究所_信息服务与智能控制技术研究室 |
| 推荐引用方式 GB/T 7714 | Wu JW,Zhu YL,Ku T,et al. A Novel Compression Algorithm for Spatiotemporal Data Based on PSO and GA[C]. 见:International Conference on Computational Intelligence and Software Engineering (CiSE 2012). Wuhan, China. December 14-16, 2012. |
入库方式： OAI收割
来源：沈阳自动化研究所
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