Using Z-number to measure the reliability of new information fusion method and its application in pattern recognition

Tian, Ye; Mi, Xiangjun; Cui, Huizi; Zhang, Pengdan; Kang, Bingyi

doi:10.1016/j.asoc.2021.107658

Cited by 22 publications

(5 citation statements)

References 57 publications

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“…At the second step, the constraint part can be weighted with , and the new fuzzy set, , occurs as a result of this process. (17) For ranking discrete fuzzy sets, H. Basirzadeh et al proposed a method in 2012 [30] . Gong Y. et al followed the same procedure to rank in their work.…”

Section: A Methods For Ranking Discrete Z-numbersmentioning

confidence: 99%

“…As another branch of work, W. Jiang et al proposed a novel method combining Z-number with Dempster -Shafer evidence theory and they made an application in sensor data fusion problem [15] . As a clustering/classifying problem, Z-number was used with fuzzy c-means and k-means clustering, respectively [16,17] . The effectiveness of the proposed methods was shown on well-known datasets such as iris dataset, wine dataset etc.…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

A Review on Ranking of Z-numbers

Bilgin

Alcı

2022

j. of Comput. sci. res.

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There are numerous studies about Z-numbers since its inception in 2011. Because Z-number concept reflects human ability to make rational decisions, Z-number based multi-criteria decision making problems are one of these studies. When the problem is translated from linguistic information into Z-number domain, the important question occurs that which Z-number should be selected. To answer this question, several ranking methods have been proposed. To compare the performances of these methods, benchmark set of fuzzy Z-numbers has been created in time. There are relatively new methods that their performances are not examined yet on this benchmark problem. In this paper, we worked on these studies which are relative entropy based Z-number ranking method and a method for ranking discrete Z-numbers. The authors tried to examine their performances on the benchmark problem and compared the results with the other ranking algorithms. The results are consistent with the literature, mostly. The advantages and the drawbacks of the methods are presented which can be useful for the researchers who are interested in this area.

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Section: A Methods For Ranking Discrete Z-numbersmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

A Review on Ranking of Z-numbers

Bilgin

Alcı

2022

j. of Comput. sci. res.

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“…In practice, different membership functions can be used to describe the numerical distribution of fuzzy variables

\tilde{A}

and

\tilde{B}

in the proposed Z ‐valuation [36]. For this research, without loss of generality, we arbitrarily assume that the uncertainties that associated with the customers’ price elasticity

{\varepsilon }_t

and its information credibility follow a trapezoidal and a triangular distribution, respectively.…”

Section: Idc Demand Response Characterizationmentioning

confidence: 99%

Quantifying the capacity credit of IDC‐based demand response in smart distribution systems

Zeng

Zhang

et al. 2023

IET Generation Trans & Dist

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With the explosive growth of online services, the Internet Data Center (IDC) has become an emerging load demand . The power consumption of IDCs are believed suitable for demand response (DR) purposes due to its temporal-spatial flexibility properties. To what extent IDCs could be used as candidate DR resources to provide capacity support are dependent both on the technical property and the willingness of data end-users . To address the above issue, this paper presents a methodological framework for quantifying the potential value of IDC-based DR in distribution grids. To achieve this, the concept of capacity credit (CC) is introduced and extended into the IDC scenario. The proposed framework explicitly considered the impacts of uncertainty of user participation intention and the reliability of basic information in the DR process. A novel Z-number based price elasticity uncertainty model is introduced, and a more realistic evaluation of IDC capacity credit is obtained. Finally, the effectiveness of the proposed model and method is illustrated on a modified IEEE-33 node network, and the obtained results verify the significance of IDC-based DR in enhancing the adequacy of supply in distribution grids.

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“…Since the thought of Z-numbers was put forward in 2011 to now, the mathematical system and application of Z-numbers have become more and more complete. In applications of Z-number, The most widespread application areas are decision-making, such as selection problems [2,10], fault diagnosis [13], pattern recognition [25], risk assessment [1]. The Z-number has been especially useful for describing calculations in natural language.…”

Section: Instructionmentioning

confidence: 99%

A Modified Uncertainty Measure of Z-numbers

Cabrerizo

Herrera‐Viedma

Morente-Molinera

2022

INT J COMPUT COMMUN, Int. J. Comput. Commun. Control

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The Z-number is a more adequate construct for describing real-life information. While considering the uncertainty of the information, it also models the partial reliability of the information. It is a combination of probabilistric restriction and possibilistric restriction. In this paper, we modified the uncertainty measurement of the discrete Z-number and proposed the uncertainty measurement of the continuous Z-number. Some numerical examples are used to illustrate the calculation processes and advantages of the proposed method. An application of journey vehicle selection shows the effectiveness of the proposed uncertainty measurement in determining the weights of criteria.

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Using Z-number to measure the reliability of new information fusion method and its application in pattern recognition

Cited by 22 publications

References 57 publications

A Review on Ranking of Z-numbers

A Review on Ranking of Z-numbers

Quantifying the capacity credit of IDC‐based demand response in smart distribution systems

A Modified Uncertainty Measure of Z-numbers

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