基于模糊聚类特征分解的数据库优化访问——以有色金属数据库为例

Based on fuzzy clustering feature decomposition of database optimization

数据库的优化访问在数据信息处理和调度中具有广泛的应用,针对当前数据库访问效率低,运行开销大的问题,提出一种基于模糊聚类特征分解的数据库优化访问算法。构建数据库中的数据信息流模糊聚类模型,进行特征分解实现数据库中信息流的分类调度,计算数据库访问过程中的相应查询数据序列的平均信息量,基于路径索引和空间划分进行访问区间匹配。仿真结果表明,该算法能提高数据库访问效率,降低数据查询时间。

The optimization of database access in the dispatching of data information processing and has wide application, in view of the current database access efficiency is low, the problem of large operation cost, put forward a kind of based on fuzzy clustering feature decomposition of accessing database optimization algorithm. Build data in the database information flow fuzzy clustering model, the classification of the characteristics of decomposition to realize database information flow scheduling, calculation in the process of database access query data sequences corresponding average amount of information, based on path indexes and space division access range matching. The simulation results show that the proposed algorithm can improve the efficiency of database access, reduce the data query time.