A New Interval Numbers Power Average Operator in Multiple Attribute Decision Making

Song, Moxian; Jiang, Wen; Xie, Chunhe; Zhou, Deyun

doi:10.1002/int.21861

Cited by 27 publications

(16 citation statements)

References 38 publications

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“…Information quality is firstly proposed by Yager and Petry based on Gini entropy to measure the uncertainty for a probability distribution [32], [33]. It has been widely used in pattern classification [34], [35], decision making [36], [37] and so on [38]- [43], [43], [44]. Li et al propose a generalized expression for information quality in basic probability assignment in Dempster-Shafer evidence theory [45], which makes information quality have greater scope of application.…”

Section: Introductionmentioning

confidence: 99%

An Improved Expression for Information Quality of Basic Probability Assignment and Its Application in Fault Diagnosis

Li¹,

Cai²

2020

Preprint

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<div>Information quality is widely used in many applications. However, how to measure information quality in basic probability assignment accurately is still an open issue. Generalized expression for information quality is an effective method to measure information quality in basic probability assignment. Nevertheless, the counter-intuitive results may be obtained when statements are of intersection. To address this issue, a new expression for information quality of basic probability assignment is proposed in this paper considering the frame of discernment and the influence of intersection among statements which can cause changes of uncertainty. Numerical examples are illustrated to demonstrate the effectiveness of the proposed method. In addition, an application in fault diagnosis is used to show the effectiveness of the proposed method. </div>

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Section: Introductionmentioning

confidence: 99%

An Improved Expression for Information Quality of Basic Probability Assignment and Its Application in Fault Diagnosis

Li¹,

Cai²

2020

Preprint

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“…Information quality is firstly proposed by Yager and Petry based on Gini entropy to measure the uncertainty for a probability distribution [24], [25]. It has been widely used in pattern classification [26], [27], decision making [28], [29] and so on [30]- [36]. Li et al propose a generalized expression for information quality in basic probability assignment in Dempster-Shafer evidence theory [37], which makes information quality have greater scope of application.…”

Section: Introductionmentioning

confidence: 99%

An Improved Expression for Information Quality of Basic Probability Assignment and Its Application in Fault Diagnosis

Li¹

2020

Preprint

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<div>Information quality is widely used in many applications. However, how to measure infor </div><div>mation quality in basic probability assignment accurately is still an open issue. Generalized expression for </div><div>information quality is an effective method to measure information quality in basic probability assignment. </div><div>Nevertheless, the counter-intuitive results may be obtained when statements are of intersection. To address </div><div>this issue, a new expression for information quality of basic probability assignment is proposed in this paper </div><div>considering the frame of discernment and the inflfluence of intersection among statements which can cause </div><div>changes of uncertainty. Numerical examples are illustrated to demonstrate the effectiveness of the proposed </div><div>method. In addition, an application in fault diagnosis is used to show the effectiveness of the proposed </div><div>method. </div>

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“…44,45 With respect to the PA operator, Jiang et al 46 aggregated linguistic values under unbalanced linguistic term sets by PA operator. Song et al 47 considered aggregating interval values by the PA operator. For the research works of the PG operator, Xu and Wang 48 constructed some new linguistic aggregation operators for GDM with PG operator.…”

Section: Introductionmentioning

confidence: 99%

q‐Rung orthopair fuzzy sets‐based decision‐theoretic rough sets for three‐way decisions under group decision making

Liang

Cao

2019

Int J Intell Syst

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As an extension of Pythagorean fuzzy sets, the q‐rung orthopair fuzzy sets (q‐ROFSs) can easily solve uncertain information in a broader perspective. Considering the fine property of q‐ROFSs, we introduce q‐ROFSs into decision‐theoretic rough sets (DTRSs) and use it to portray the loss function. According to the Bayesian decision procedure, we further construct a basic model of q‐rung orthopair fuzzy decision‐theoretic rough sets (q‐ROFDTRSs) under the q‐rung orthopair fuzzy environment. At the same time, we design the corresponding method for the deduction of three‐way decisions by utilizing projection‐based distance measures and TOPSIS. Then, we extend q‐ROFDTRSs to adapt the group decision‐making (GDM) scenario. To fuse different experts’ evaluation results, we propose some new aggregation operators of q‐ROFSs by utilizing power average (PA) and power geometric (PG) operators, that is, q‐rung orthopair fuzzy power average, q‐rung orthopair fuzzy power weighted average (q‐ROFPWA), q‐rung orthopair fuzzy power geometric, and q‐rung orthopair fuzzy power weighted geometric (q‐ROFPWG). In addition, with the aid of q‐ROFPWA and q‐ROFPWG, we investigate three‐way decisions with q‐ROFDTRSs under the GDM situation. Finally, we give the example of a rural e‐commence GDM problem to illustrate the application of our proposed method and verify our results by conducting two comparative experiments.

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A New Interval Numbers Power Average Operator in Multiple Attribute Decision Making

Cited by 27 publications

References 38 publications

An Improved Expression for Information Quality of Basic Probability Assignment and Its Application in Fault Diagnosis

An Improved Expression for Information Quality of Basic Probability Assignment and Its Application in Fault Diagnosis

An Improved Expression for Information Quality of Basic Probability Assignment and Its Application in Fault Diagnosis

q‐Rung orthopair fuzzy sets‐based decision‐theoretic rough sets for three‐way decisions under group decision making

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