ZSLF: A New Soft Likelihood Function Based on Z-Numbers and Its Application in Expert Decision System

Due to the complexity of the real world, effective consideration of the ambiguity and reliability of information is a challenge that must be addressed by the correct decision of the expert system. Z-number provides us with a good idea because it describes the probability of the random variable and the possibility measure. Recently, Yager presented a soft likelihood function that effectively combines probabilistic evidence to deal with the conflict information. This article generalizes Yager's soft likelihood function based on Z-numbers and proposes a Z-numbers soft likelihood function (ZSLF) decision model. The application examples show the rationality and effectiveness of the method. The comparison and discussion further show the advantages of the ZSLF decision model.

Automated summary

This article presents a Z-numbers soft likelihood function (ZSLF) decision model based on Yager's soft likelihood function, which effectively combines probabilistic evidence to handle conflicting information. Application examples demonstrate the rationality and effectiveness of the method, while comparisons and discussions further highlight the advantages of the ZSLF decision model.