Bipolar Complex Fuzzy Hamacher Aggregation Operators and Their Applications in Multi-Attribute Decision Making

Mahmood, Tahir; Rehman, Ubaid ur; Ahmmad, Jabbar; Santos‐García, Gustavo

doi:10.3390/math10010023

Cited by 37 publications

(32 citation statements)

References 53 publications

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“…Next, notice from Table XV, that the prevailing operators Hamacher operators for BCF set theory was diagnosed by Mahmood et al [44], and Dombi operators for BCF set theory were evaluated by Mahmood and Ur Rehman [35]. are providing the results here.…”

Section: Comparative Analysismentioning

confidence: 94%

“…In this article, the set Ќ = (Η 𝑃−Ќ (𝔟), Η 𝑁−Ќ (𝔟)) = (Η 𝑅𝑃−Ќ (𝔟) + 𝜄Η 𝐼𝑃−Ќ (𝔟), Η 𝑅𝑁−Ќ (𝔟) + 𝜄 Η 𝐼𝑁−Ќ (𝔟)) will appear for BCF numbers (BCFNs). Definition 3: [44] The score value (SV) of any BCFN is declared as…”

Section: A Frank T-norm and T-conormmentioning

confidence: 99%

“…Finally, we compared the diagnosed operators with various existing theories to improve the worth of the invented approaches. Enhancing the worth of the diagnosed operators with the help of comparative analysis, for this, we selected some prevailing theories explained in Ref [25,43,58,59,60,44,45]. The comparative result of the diagnosed operators with selected prevailing theories is explained in Table XV.…”

Section: Comparative Analysismentioning

confidence: 99%

“…With the help of BCFS, experts very easily determined our main target, which was impossible under the consideration of BFS information. Certain applications of the BCFS have been done by distinct intellectuals [44,45].…”

Section: Introductionmentioning

confidence: 99%

“…To evaluate this sort of data we need the conception of BCFS which is very valuable and a handful to handle such sort of data. Numerous authors have defined aggregation operators (AOs) in the setting of BCF theory such as [44,45,46] but these AOs based on t-norm and t-conorm are not very accommodating to contain all data to structure real-life issues. Due to this, Frank [47] introduced Frank t-norms and Frank t-conorms by modifying the Lukasiewicz and Probabilistic t-norm and t-conorm which is an accommodating class of norms and conorms.…”

Section: Introductionmentioning

confidence: 99%

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Identification and Prioritization of DevOps Success Factors Using Bipolar Complex Fuzzy Setting With Frank Aggregation Operators and Analytical Hierarchy Process

et al. 2022

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DevOps ("development and operations") is a dominant and collaborative organizational effort to computerize simultaneously the supply of a software strategy with a theme to enhance software features. The usage of the DevOps technique is not an easy task as there is various vagueness involved with it. The main goal of this analysis is to employ the Frank t-norm and t-conorm (which is an accommodating class of norms and conorms and due to the parameters the Frank t-norm and t-conorm become more flexible in the combining the data and appropriate to address the real-life issues) in the environment of bipolar complex fuzzy theory to handle the DevOps procedures. Moreover, we define Frank's operational laws and their appropriate result employing BCF information. Then, we establish, the bipolar complex fuzzy (BCF) Frank weight averaging (BCFFWA), BCF Frank ordered weight averaging (BCFFOWA), BCF Frank hybrid weight averaging (BCFFHWA), BCF Frank weight geometric (BCFFWG), BCF Frank ordered weight geometric (BCFFOWG), BCF Frank hybrid weight geometric (BCFFHWG) operators and assess certain properties and results. Furthermore, we find the major factors that positively influence the DevOps technique in software organizations. In the presence of the prevailing information, nineteen factors were diagnosed. The diagnosed features were moreover authorized by intellectuals via hypothetical information. Finally, BCF analytical hierarchy process (BCFAHP) technique is invented to prioritize the classification success features. The final ranking mentioned that "DevOps security pipeline", "use system orchestration", and "attempt matrix organization and transparency" features are the beneficial ranked success features for the valuable utilization of DevOps techniques. Finally, we compare the diagnosed operators with various existing theories to improve the worth of the invented approaches.

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Section: Comparative Analysismentioning

confidence: 94%

Section: A Frank T-norm and T-conormmentioning

confidence: 99%