Results 151 to 160 of about 6,799,493 (191)

Development of a triangular Fermatean fuzzy EDAS model for remote patient monitoring applications. [PDF]

Sci Rep
Khan A, Islam S, Ismail M, Alotaibi A.
europepmc   +1 more source

An integrated neutrosophic Z-numbers based CRITIC-EDAS decision model for smart solar panel evaluation in sustainable energy planning. [PDF]

Sci Rep
Abbas MZ, Anjum R, Hussain A, Ahmad M, Haleemzai I.   +4 more
europepmc   +1 more source

Maintenance strategy selection for engineering systems based on multi-criteria decision making approach by using bipolar complex fuzzy prioritized aggregation operators. [PDF]

Sci Rep
Xu Z, Rehman UU, Mahmood T, Zeng S.
europepmc   +1 more source

Photon-Counting CT for Evaluation of Coiled Intracranial Aneurysms. [PDF]

AJNR Am J Neuroradiol
Mac Grory B, Randles A, Urick DM, Schwartz FR, Hasan D, Calabrese ED.   +5 more
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AI simulation models for diagnosing disabilities in smart electrical prosthetics using bipolar fuzzy decision making based on choquet integral. [PDF]

Sci Rep
Rehman UU, Khan MA, Aldayel OA, Mahmood T.   +3 more
europepmc   +1 more source

A cubical fuzzy Dubois-Prade aggregation framework for renewable and sustainable green energy decision-making. [PDF]

Sci Rep
Deva K, Sangeetha S, Tolasa FT, Olana JA, Tamune SA.   +4 more
europepmc   +1 more source

An extended CoCoSo method under (p-q) rung orthopair fuzzy environment for multi-criteria decision-making applications. [PDF]

Sci Rep
Khan A, Barukab O, Jun YB, Khan SA, Ahmad U, Rushdi AMA.   +5 more
europepmc   +1 more source

Federated edge-AI for reliable and privacy-preserving pipeline leak detection in drone swarms using neutrosophic sugeno-weber norms. [PDF]

Sci Rep
Zulqarnain RM, Hameed MS, Saeedi G, Hashmi MA, Noreen E, Kamran M, Simic V.   +6 more
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Innovative impact of artificial intelligence and management in rural revitalization under fuzzy based decision-making approach. [PDF]

Sci Rep
Wang M, Zhang H, Zhao H.
europepmc   +1 more source

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Determining the membership degrees in the range (0, 1) for hypersoft sets independently of the decision-maker

International Journal of Systems Science, 2022
Today, Molodtsov's soft set has been generalised to hypersoft sets, and the use of hypersoft set theory for uncertain data has become more preferable than soft sets. However, the membership degree of an object in hypersoft sets is 0 or 1.
Orhan Dalkilic
exaly   +2 more sources