A Multi-attribute Decision Making Method Based on Interval Pythagorean Fuzzy Language and the PROMETHEE Method

Zhang, Wenyu; Zhu, Yuting; Wang, Danshu; Zhao, Songmin; Dong, Dadi

doi:10.1007/978-3-030-32456-8_88

Cited by 2 publications

(2 citation statements)

References 6 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Therefore, 𝒖𝒖 𝒏𝒏,𝒊𝒊 and 𝝈𝝈 𝒏𝒏,𝒊𝒊 can be adjusted using the constrained GA to improve the accuracy of the fault diagnosis model. According to equations ( 23)- (24) and equation (26), the objective function and constraints to be optimized are as follows:…”

Section: Fault Diagnosis Flow Based On the Ger-g Modelmentioning

confidence: 99%

“…In 2013, Yang and Xu proposed the ER rule [23]. It has been widely used in evaluation and decision-making, including multi-attribute decision analysis [24], information fusion [25] [26], and expert systems [27] [28]. In this paper, the ER rule is utilized to fuse the dissolved gases in the oil to identify different degrees of faults in oil-immersed transformers.…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

A New Method for Oil-Immersed Transformers Fault Diagnosis Based on Evidential Reasoning Rule With Optimized Probabilistic Distributed

E.,

Zhang,

et al. 2024

IEEE Access

View full text Add to dashboard Cite

Power transformers are important equipment in power systems. Most medium and large transformers are oil-immersed transformers, with the exception of some small-and medium-capacity transformers and gas transformers with special purpose. It is extremely critical to detect malfunction timely and accurately, because the reliability and safety of oil-immersed transformers can cause significant implications for power systems. Therefore, the fault diagnosis model based on the evidential reasoning (ER) rule with reference points in the Gaussian distribution form optimized by a constrained genetic optimization algorithm (GA), named GER-G model, is proposed in this paper. The GER-G fault diagnosis model can monitor and identify the degree of transformer faults in real time. First, the concentration of dissolved gases in the oil of oil-immersed transformers varies at different fault degrees, so the gases with high weight are selected using the maximum correlation-minimum redundancy (mRMR) to constitute the indicator system. Second, to solve the uncertainty existing in the fault information of transformers, the reference points of the ER rule are continuous probability distribution reference points described by Gaussian distribution form. Third, the constrained GA is proposed to adapt the Gaussian distribution. And the accuracy of fault diagnosis results can be enhanced by optimizing the grade parameters using constrained GA. Finally, the internal and external influences in the environment are quantified using perturbation analysis, the GER-G fault diagnosis model is applied to the dataset of dissolved gases in the oil, and the robustness and validity of the GER-G fault diagnosis model are validated. Meanwhile, the validation results also show that the GER-G fault diagnosis model possesses higher accuracy compared with other fault diagnosis methods.

show abstract

Section: Fault Diagnosis Flow Based On the Ger-g Modelmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

A New Method for Oil-Immersed Transformers Fault Diagnosis Based on Evidential Reasoning Rule With Optimized Probabilistic Distributed

E.,

Zhang,

et al. 2024

IEEE Access

View full text Add to dashboard Cite

show abstract

A Novel Pythagorean Fuzzy Extension of DEMATEL and Its Usage on Overcoat Selection Attributes for Antarctic Clothing

Sivri

Gül

Aksu

2022

Int. J. Info. Tech. Dec. Mak.

View full text Add to dashboard Cite

Scientific explorations and research in the Antarctic region have specific issues which need to be handled with special measures. Clothing of the scientists is one of the main problems. The clothes are expected to be enduring against compelling conditions and they must have certain features to ensure the safety and comfort of the scientists. Polar clothing is a field that is yet to be studied with different engineering approaches. To generate a better understanding, the polar clothing can be approached as a multiple criteria decision-making problem because many criteria such as layer number, material type, and waterproofness should be considered while evaluating the various alternatives. In this evaluation, expert judgments are used because no strict objective rules determine the conditions of the polar clothing. Also, possible influences among these criteria should be revealed and considered while reaching a decision. In order to deal with the uncertainty and vagueness of the expert judgments, this study proposes a Pythagorean fuzzy version of DEMATEL which is one of the well-known multiple criteria decision-making tools with the aim of evaluating the related selection attributes affecting the decision and searching for the potential influences among them. Since Pythagorean fuzzy sets provide a wider preference domain to the experts, this version was developed as a contribution to the literature. Also, the decision process is kept Pythagorean fuzzy until a conclusion is reached so that there is no early defuzzification problem. The method’s application on overcoat selection for the Antarctic region reveals the relations among attributes, such as “Water Vapor Permeability”, “All-Weather Protection” and “Performing Best in Dry/Wet State”. A sensitivity analysis is conducted to find the changes in influences.

show abstract

A Multi-attribute Decision Making Method Based on Interval Pythagorean Fuzzy Language and the PROMETHEE Method

Cited by 2 publications

References 6 publications

A New Method for Oil-Immersed Transformers Fault Diagnosis Based on Evidential Reasoning Rule With Optimized Probabilistic Distributed

A New Method for Oil-Immersed Transformers Fault Diagnosis Based on Evidential Reasoning Rule With Optimized Probabilistic Distributed

A Novel Pythagorean Fuzzy Extension of DEMATEL and Its Usage on Overcoat Selection Attributes for Antarctic Clothing

Contact Info

Product

Resources

About