基于联合邻域的粗糙集模型

Priti Madan, Alka Tripathi
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引用次数: 0

摘要

提出了粗糙集思想作为处理信息系统中数据的模糊性或不确定性的一种方法。邻域(nbd)系统是减小边界面积、提高测量精度的重要工具。本文主要介绍了一类新的并集nbd(简写为???? -nbd),并建立了它们的性质。这些? ?应用j -nbd得到????的概念下近似和????上近似,和????ʝ准确性的措施。提出了它们的性质。最后以医疗应用????的意义进行论证给出了[-nbds]
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Rough Set Model based on Union Neighborhood
The rough set idea was presented asan approach to deal with the ambiguity or uncertainty of the data in information systems. The neighborhood (nbd) system is an essential tool for reducing the boundary area and increasing the accuracy of the measurement. The main focus of the present paperis to introduce the new type of union nbds (briefly, ????ʝ-nbds) and to establish their properties. These ????ʝ-nbds are applied to obtain the concept of ????ʝ-lower approximation and ????ʝ-upper approximation, and ????ʝ-accuracy measure. Their properties are proposed. Finally, a medical application to demonstrate the significance of ????ʝ-nbds is presented
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