The total uncertainty measurement of basic probability assignment (BPA) in evidence theory has always been an open issue. Although many scholars have put forward various measures and requirements of bodies of evidence (BoE), none of them are widely recognized. So in order to express the uncertainty in evidence theory, transforming basic probability assignment (BPA) into probability distribution is a widely used method, but all the previous methods of probability transformation are directly allocating focal elements in evidence theory to their elements without specific transformation process. Based on above, this paper simulates the pignistic probability transformation (PPT) process based on the idea of fractal, making the PPT process and the information volume lost during transformation more intuitive. Then apply this idea to the total uncertainty measure in evidence theory. A new belief entropy called Fractal-based (FB) entropy is proposed, which is the first time to apply fractal idea in belief entropy. After verification, the new entropy is superior to all existing total uncertainty measurements.
翻译:证据理论中基本概率分配(BPA)的全面不确定性测量始终是一个未决问题。虽然许多学者提出了各种证据(BoE)的计量和要求,但其中没有一个得到了广泛承认。因此,为了表达证据理论的不确定性,将基本概率分配(BPA)转化为概率分布是一种广泛使用的方法,但所有先前的概率转换方法都直接将证据理论中的焦点元素与其元素分配,而没有具体的转化过程。基于以上,本文模拟了基于分形概念的光概率转换(PPPT)过程,使PPPT过程和在转换过程中丢失的信息量更加直观。然后在证据理论中将这一想法应用到整个不确定性计量中。提出了一种称为基于Factal(FB)的新的信灵的加密,这是首次在信念中应用折变方概念。根据以上,新的正本优于所有现有的全部不确定性测量。