Evidence combination using OWA‐based soft likelihood functions

Liguo Fei · Yuqiang Feng · Luning Liu

58 citations0/0 files storedInternational Journal of Intelligent Systems

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Multi-Criteria Decision Making Rough Sets and Fuzzy Logic Fuzzy and Soft Set Theory

Abstract

Dempster's combination rule has been widely regarded and applied since it is an effective and rigorous method of synthesizing multisource information with its special information representation (ie, mass function or basic probability assignment). However, it has also been criticized and debated upon regarding some of its unreasonable behaviors and restrictive requirements, such as the counterintuitive results in some cases. To address these issues from different perspectives, in this study, an alternative fusion rule is developed under the framework of Dempster-Shafer evidence theory. A novel evidence combination rule called CR-SLF is proposed based on soft likelihood functions (SLF) considering the ordered weighted average aggregation operator. Some illustrative examples are shown, and the corresponding analyses demonstrate the good performance of CR-SLF to fuse multisource evidence. To extend CR-SLF further, the reliability of multisource evidence is considered from two aspects, subsequently two reliability-based combination rules are presented, including the discount-based rule and the SLF improvement-based rule. The simulation results show that the reliability-based CR-SLF has a better fusion effect than the rule without considering the reliability.

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References

1965Fuzzy sets 1988On ordered weighted averaging aggregation operators in multicriteria decisionmaking 1981Methods for Multiple Attribute Decision Making 1987On the dempster-shafer framework and new combination rules 1998Quantifier guided aggregation using OWA operators 2000Combining belief functions when evidence conflicts 2001A new distance between two bodies of evidence 2005An overview of methods for determining OWA weights

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2021A dynamic framework of multi-attribute decision making under Pythagorean fuzzy environment by using Dempster–Shafer theory 2019On Pythagorean fuzzy decision making using soft likelihood functions 2020Determining Weights in Multi-Criteria Decision Making Based on Negation of Probability Distribution under Uncertain Environment 2020Self-adaptive combination method for temporal evidence based on negotiation strategy 2020Failure mode and effect analysis using multi‐linguistic terms and Dempster–Shafer evidence theory

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