• 中国计算机学会会刊
  • 中国科技核心期刊
  • 中文核心期刊

J4 ›› 2016, Vol. 38 ›› Issue (02): 312-317.

• 论文 • 上一篇    下一篇

基于遗传算法的时空数据压缩策略优化

钱景辉,王杉杉   

  1. (南京工业大学计算机科学与技术学院,江苏 南京 211816)
  • 收稿日期:2015-03-13 修回日期:2015-07-10 出版日期:2016-02-25 发布日期:2016-02-25

Optimization of compression strategy for
spatio-temporal data based on genetic algorithms 

QIAN Jinghui,WANG Shanshan   

  1. (College of Computer Science and Technology,Nanjing University of Technology,Nanjing 211816,China)
  • Received:2015-03-13 Revised:2015-07-10 Online:2016-02-25 Published:2016-02-25

摘要:

针对时空数据因为有损压缩导致的还原精度不高的问题,提出了使用遗传算法对时空数据压缩策略进行优化。算法模拟生物进化过程,首先,在初始阶段,根据所处数据环境在格拉斯普克算法基础上自适应地调整压缩参数,进行染色体编码,初始种群生成;然后在进化阶段,引入“精英保留策略”保证全局最优个体;最后完成交叉、变异等操作。采用四种不同的压缩策略进行实验,对比了各自压缩率和还原误差的详细情况。实验结果表明,遗传算法对于时空数据压缩的策略优化具有良好的效果,可以有效地降低还原误差。

关键词: 遗传算法, 时空数据, 有损压缩, 地理信息系统, 策略优化, 精英保留策略

Abstract:

For the low accuracy of recovery caused by loss compression of spatiotemporal data, we propose a genetic algorithm to optimize the compression of spatiotemporal data. On the basis of DouglasPeucker algorithm, the data environment can adjust the compression parameters adoptively, encodes the chromosomes, and generates the initial population. Secondly, at the evolution phase, the elitist strategy is adopted to obtain the global optimal individuals. Finally, crossover and mutation operations are done. We adopt four different compression strategies for the experiment, and compare the details of the compression ratio and average deviation.Experimental results show that the proposal has a good effect on the optimization of spatiotemporal data compression, and can efficiently decrease the recovery error.

Key words: genetic algorithm;spatiotemporal data;loss compression;geographic information system;optimization strategy;elitist strategy