大型数据库中信息资源利用率优化管理仿真

Optimal Management of Information Resource Utilization in Large Databases

对大型数据库中信息资源利用率进行优化管理,需要给出多个未知数据变量的估计值,通过未知数据变量间的距离差确定其权重,完成资源利用率的优化。传统方法先计算反空间假频信息资源倾角模式,对缺失信息资源进行反假频利用率管理,但忽略了确定未知数据权重,导致对利用率的管理精度偏低。提出基于紧支径向基函数的大型数据库中信息资源利用率优化方法。该方法先利用紧支径向基函数局部径向点插值方法将大型数据库中原始数据组织变换为具有一个结构化的数据模式,抽取部分数据对多维空间进行重构,计算出数据的线性函数斜率,对数据未知变量进行插值,给出多个未知数据变量的估计值,通过未知数据变量间的距离差确定其权重,完成对大型数据库中信息资源利用率优化。实验结果表明,所提方法利用率管理精度较高。

An optimization method for utilization ratio of information resource in large database is proposed based on compactly supported radial basis function. Firstly, the original data organization in large database is converted into a structured data pattern via local radial point interpolation method of compactly supported radial basis function and part of data is extracted to carry out reconstitution for multi-dimensional space. Then, slope of linear function of data is worked out and interpolation is carried out for unknown variable of data. Moreover, the estimated value of several unknown variable of data is provided and its weight is confirmed via distance difference among the unknown variables of data. Finally, the optimization of utilization ratio is completed. Experimental results show that the method has high precision of utilization ration management.