基于结构粒化的数据合并方法

Data combination method based on structure's granulation

为了研究实际中的数据合并问题,对各类数据信息给予了整体表示,使数据集、关联关系和划分共同组成了关联组合结构,为数据合并作了结构化的准备。进而,通过对关联关系的粒化处理,实现了关联组合结构到粒化结构的转换,促成了相关数据的按组合并。由于关联组合结构和粒化结构均与关联矩阵相互对应,所以基于结构转换的数据合并又可通过矩阵变换计算完成。因此所展开的讨论既包含了数据合并的理论分析,也给出了数据合并可程序化的数据形式,形成了以结构粒化为理论支撑、以矩阵变换为算法构成的数据合并方法。基于该方法的程序设计使数据合并实现了程序化,并保证了运行的线性复杂度。实验表明,理论支撑下的程序处理具有快速及准确的运行特性。

In order to study the problem about data combinations occurring in real life, different kinds of data information were combined together, leading to a structure called associated-combinatorial structure. Actually, the structure was constituted by a data set, an associated relation and a partition. The aim was to use the structure to set up a method of data combination. To this end, the associated-combinatorial structure was transformed into a granulation structure by granulating the associated relation. In this process, data combinations were completed in accordance with the data classifications. Moreover, because an associated-combinatorial structure or a granulation structure could be represented by the associated matrix, the transformation from a structure to another structure was characterized by algebraic calculations determined by matrix transformations. Therefore, the research not only involved theoretical analysis for the data combination, but also established the data processing method connected with matrix transformations. Accordingly, a computer program with linear complexity was formulated according to the data combinations method. The experimental result proves that the program is accurate and fast.