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