数据库时空选择性查询的灰色预测法

A grey estimator for spatiotemporal database selective queries

提出了一种时空选择性查询的灰色预测法,采用自适应多维直方图对当前数据库时间上各对象的分布进行概括,用于时空选择性的快速估算;利用灰色预测模型GM(1,1)根据各个历史时间点上的查询值进行预测和估计.尽管单个时空对象的运动情况包含较大的随机性,但是大量对象的整体分布是随时间稳定变化的,利用灰预测模型可降低单个对象运动情况的高随机性对整体查询结果的影响.仿真实验结果表明本方法具有较好的精确度和稳定性.

A histogram-based grey estimator for spatiotemporal selectivity estimation was introduced,adaptive multi-dimensional histogram（AMH） was used to summarize the distribution of spatial objects on the current database time,grey model GM（1,1） was used to predict near future query result through calculating history query result.Although the individual object＇s movements has much randomness,the overall data distribution varies gradually with time,due to the continuity of movement.The modal presented can reduce the effect individual randomness imposed on the overall query result.Simulations and experiments show that as randomness of history query results increasing,the near future prediction results of spatiotemporal window queries remain accurate and stable.