Fusion of qualitative beliefs based on linguistic labels

Jian Gao, Weitai Liang, Jing-Jing Yan
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Abstract

In order to model beliefs expressed by natural language, the qualitative belief assignment based on the linguistic labels has been presented in the Dezert-Smarandache Theory (DSmT). However, the combination of qualitative beliefs is only based on the equidistant linguistic labels and the calculation of non-equidistant labels is approximate. To solve the fusion problem of qualitative beliefs denoted by non-equidistant labels, this paper proposed the universal arithmetic operations of linguistic labels, and analyzed the fusion of qualitative beliefs based on the general labels. The new operations which were based on the linear or nonlinear mapping relationship between linguistic labels and numerical values, could be effectively used on 1-tuple or 2-tuple linguistic representation model, and could increase the precision and reliability of the combination of qualitative beliefs or mixed beliefs. The experimental results have proved the validity of universal operations.
基于语言标签的定性信念融合
为了对自然语言表达的信念进行建模,Dezert-Smarandache理论(DSmT)提出了基于语言标签的定性信念分配。然而,定性信念的组合仅基于等距语言标签,非等距语言标签的计算是近似的。为了解决非等距标签表示的定性信念融合问题,提出了语言标签的通用算术运算,并分析了基于一般标签的定性信念融合问题。基于语言标签与数值之间的线性或非线性映射关系的新操作可以有效地用于一元组或二元组语言表示模型,并可以提高定性信念或混合信念组合的精度和可靠性。实验结果证明了通用运算的有效性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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