CAJ | 학술논문

提出了一种标准粗糙集约简时连续属性离散化的新方法。采用标准粗糙集进行属性约简时，要求属性为离散的，而大多数情况下属性是连续的，因此需要进行离散化处理。首先介绍了原有的信息熵算法并指出其局限性；其次，对多类别信息熵进行扩充，将距离因素引入到该信息熵的计算中；最后给出了扩展信息熵计算的两个基本准则，利用证据理论完成信度的上聚焦。仿真显示了该方法的有效性。
제출료일충표준조조집약간시련속속성리산화적신방법。채용표준조조집진행속성약간시，요구속성위리산적，이대다수정황하속성시련속적，인차수요진행리산화처리。수선개소료원유적신식적산법병지출기국한성；기차，대다유별신식적진행확충，장거리인소인입도해신식적적계산중；최후급출료확전신식적계산적량개기본준칙，이용증거이론완성신도적상취초。방진현시료해방법적유효성。
A new discretized approach for continuous attributes was presented. As we know, the basic rough set theory can not deal with continuous attributes, so the continuous attributes need to be discretization. Firstly, the disadvantages of original information entropy were analyzed. Secondly, the distance factor was introduced to expand the information entropy. At last two basic rules were presented to calculate expanded information entropy and DS evidential theory was used to process the mass up﹣focus. Simulation results show the availability of this new information fusion algorithm.