CAJ | 학술논문

传统的粗糙集下挖掘算法挖掘能力有限，当海量数据类型多样化时，数据挖掘性能下降。提出一种基于绕点旋度修正的粗糙集下挖掘算法，在数据挖掘时，采用绕点的方法代表系统挖掘中的每个元素点，对于每个绕点，采用旋度评价的方法实现加权修正，通过绕点旋度修正的方法对所有的数据进行融合处理，提取出具体特征，建立数据库，采用迭代方法最大限度的提高挖掘性能。最后采用一组64维度的复杂数据进行测试实验，结果显示，基于绕点旋度修正的数据挖掘能够在大批量多样性数据时实现很好的数据挖掘，具有工程使用价值。
전통적조조집하알굴산법알굴능력유한，당해량수거류형다양화시，수거알굴성능하강。제출일충기우요점선도수정적조조집하알굴산법，재수거알굴시，채용요점적방법대표계통알굴중적매개원소점，대우매개요점，채용선도평개적방법실현가권수정，통과요점선도수정적방법대소유적수거진행융합처리，제취출구체특정，건립수거고，채용질대방법최대한도적제고알굴성능。최후채용일조64유도적복잡수거진행측시실험，결과현시，기우요점선도수정적수거알굴능구재대비량다양성수거시실현흔호적수거알굴，구유공정사용개치。
In traditional data mining algorithm, the mining capability was limited by the vast diversity of data types, and the data mining performance was declined significantly. So the data mining algorithm under rough set was proposed based on rotation around point correction, the method of digging around the point on behalf of each element in the system of points was used, for each point around, the way of spin evaluation was carried out to achieve a weighted correction, so the rotation around the point correction method for all data integration processing was extracted with the specific characteristics, and the database was established, with the purpose of approaching maximize mining properties. Finally, a group of 64-dimen-sional complex data was used to do test experiment, and the result shows that with rotation around point correction mining method, a good data mining result in large quantities around the diversity of data points was achieved, so it has good appli-cation value for data mining.