Dempster-Shafer evidence theory is widely used in information fusion. However, it may lead to an unreasonable result when dealing with high conflict evidence. In order to solve this problem, we put forward a new method based on the credibility of evidence. First, a novel belief entropy, Deng entropy, is applied to measure the information volume of the evidence and then the discounting coefficients of each evidence are obtained. Finally, weighted averaging the evidence in the system, the Dempster combination rule was used to realize information fusion. A weighted averaging combination role is presented for multi-sensor data fusion in fault diagnosis. It seems more reasonable than before using the new belief function to determine the weight. A numerical example is given to illustrate that the proposed rule is more effective to perform fault diagnosis than classical evidence theory in fusing multi-symptom domains.

Atanassov's intuitionistic fuzzy set (IFS) is a generalization of a fuzzy set that can express and process uncertainty much better. There are various averaging operators defined for IFSs. In this paper, a new type of operator called an intuitionistic fuzzy entropy weighted power average ggregation operator is proposed. The entropy among IFSs is taken into consideration to determine the weights. What's more, the similarity is considered to measure the support degree between two elements of the IFS. Compared with other classical power average operators, the proposed operator is completely driven by data and fully takes into account the relationship among values. Finally, an illustrative example of multiple attribute group decision making is presented to show that the proposed operator is effective and practical. C 2017 Wiley Periodicals, Inc.

Failure mode and effects analysis is an important methodology, which has been extensively used to evaluate the potential failures, errors, or risks in a system, design, or process. The traditional method utilizes the risk priority number ranking system. This method determines the risk priority number by multiplying failure factor values. Dempster-Shafer evidence theory has been combined with failure mode and effects analysis due to its effectiveness in dealing with uncertain and subjective information. However, since the risk evaluation of different experts may be different and some even conflict with each other, Dempster's combination rule may become invalid. In this article, for better performance of application of evidence theory in failure mode and effects analysis, a modified method is proposed to reassign the basic believe assignment taking into consideration a reliability coefficient based on evidence distance. We illustrate several numerical examples and use the modified method to obtain the risk priority numbers for risk evaluation in failure modes of aircraft engine rotor blades. The results show that the proposed method is more reasonable and effective for real applications. KeywordsDempster-Shafer evidence theory, failure mode and effects analysis, risk priority number, basic believe assignments, reliability coefficient, aircraft turbine rotor blades Date

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