油库安全模糊评价的隶属度转换新方法

Kai-di Liu, Jin Wang, Yan-jun Pang
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引用次数: 0

摘要

为了实现储油安全评价,清除指标隶属度中对目标分类没有帮助的冗余数据,基于熵的数据挖掘,挖掘隐藏在各个指标中的对象分类知识信息,确定对象分类与指标隶属度的关系,通过定义可区分的权重,消除指标隶属度中用于对象分类的冗余数据,提取有效值计算对象隶属度。本文以储油安全为例。实证结果表明:为了消除冗余数据的干扰,将多指标属性下的隶属度转换作为有效方法。基于熵的数据挖掘方法消除了模糊评价中冗余数据的干扰,解决了多指标决策问题。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
A New Method of Membership Conversion for Fuzzy Evaluation of the Oil Storage Safety
In order to realize evaluation of oil storage safety, clear the redundant data in indexes membership which is not useful for goal classification, based on data mining of entropy, mining knowledge information about object classification hidden in every index, affirming the relation of object classification and index membership, eliminating the redundant data in index membership for object classification by defining distinguishable weight, extracting valid values to compute object membership. A case of oil storage safety is in this paper. Empirical results show that: In order to clear the interference of redundant data, the membership conversion will be used as valid method with multiple indexes attributes. The method based on data mining of entropy clear the interference of redundant data in fuzzy evaluation and many multiple indexes decision-making are solved.
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