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arXiv 0807.3483cs.AI
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用低复杂度的实用编码实现一般置信函数框架

Implementing general belief function framework with a practical codification for low complexity

DRDC (Defense Research and Development Canada)(加拿大国防研究与发展部);ENSIETA(法国国立高等工程技术学校(布雷斯特))

Arnaud Martin

摘要:

在这一章中,我们提出了一个新的实用的文氏图的元素编码,以方便地操纵焦点元素。为了减少复杂性,最终的限制必须在开始时纳入编纂。因此,我们只考虑可以是$2^Θ$或$D^Θ$的简化超幂集$D_r^Θ$。我们描述了一个一般的信念函数框架的所有步骤。决策的步骤是特别研究,事实上,当我们可以决定的识别空间的单态的交叉点没有实际的决策函数是很容易使用的。因此,提出了两种办法,一种是对前一种办法的扩展,另一种是根据要作出决定的要素的具体情况。本章的主要目的是为需要信度函数理论的研究者和用户提供一个通用信度函数框架的实用代码。

英文摘要:

In this chapter, we propose a new practical codification of the elements of the Venn diagram in order to easily manipulate the focal elements. In order to reduce the complexity, the eventual constraints must be integrated in the codification at the beginning. Hence, we only consider a reduced hyper power set $D_r^Θ$ that can be $2^Θ$ or $D^Θ$. We describe all the steps of a general belief function framework. The step of decision is particularly studied, indeed, when we can decide on intersections of the singletons of the discernment space no actual decision functions are easily to use. Hence, two approaches are proposed, an extension of previous one and an approach based on the specificity of the elements on which to decide. The principal goal of this chapter is to provide practical codes of a general belief function framework for the researchers and users needing the belief function theory.

机构、总结、中文摘要均由AI分析而来,可能存在错误,请以论文正文为准。

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