许多时空应用(如火灾模拟等)需要高效地查询移动对象的变化范围,针对此需求提出了基于TPR-tree和GF索引方法的两种混合索引结构,以支持对移动对象当前和未来范围的预测时空查询.在代价模型分析的基础上,基于模拟数据集的实验结果表明,这种混合索引方法能够有效地支持对移动对象变化范围的预测查询.
Many spatiotemporal applications such as fire simulation need to efficiently query the changing extents of continuously moving objects. Two hybrid index structures based on TPR-tree and GF were proposed to support the spatiotemporal predictive querying of current and predicted future extents. Based on cost analysis, experimental results performed on simulated datasets show that the proposed index structures are effective for the predictive querying of the extents of moving objects.