Neutrosophic sets and hypersoft sets are both fuzzy set extensions that deal with various aspects of uncertainty and missing data. Combining these two frameworks within Multi-Criteria Decision-Making (MCDM) allows choosing an optimal solution from a wide
Ahmad, Adil +4 more
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Assessing Teaching Effectiveness in Journalism and Communication: A Data-Driven Perspective Using HyperSoft Set [PDF]
Teaching effectiveness in Journalism and Communication plays a vital role in preparing students for the rapidly evolving media landscape. Traditional lecture-based approaches are increasingly being replaced by interactive, technology-enhanced teaching ...
Xiaoxi Zhang
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Hypersoft Sets in a Game Theory-Based Decision Making Model
In this study, we offer a hypersoft set theory-based game model for handling uncertainties. The term “hypersoft game” refers to this newly suggested game. Four techniques of game solution are identified: hypersoft saddle points, hypersoft upper and lower
Amsaveni, M. +2 more
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TreeSoft Set vs. HyperSoft Set and Fuzzy-Extensions of TreeSoft Sets
HyperSoft Set Methods in EngineeringThe TreeSoft Set is more general than the HyperSoft Set. The TreeSoft Set is a union of HyperSoft Sets. To distinguish between the levels of attributes, we use the comma notation i.e. an attribute of level k has k-1 commas in between its indexes.
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An algorithmic multiple attribute decision-making method for heart problem analysis under neutrosophic hypersoft expert set with fuzzy parameterized degree-based setting. [PDF]
PeerJ Comput Sci, 2023 Ihsan M, Saeed M, Alanzi AM, Khalifa HE.
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Theoretical framework for a decision support system for micro-enterprise supermarket investment risk assessment using novel picture fuzzy hypersoft graph. [PDF]
PLoS One, 2023 Saeed M, Harl MI, Saeed MH, Mekawy I.
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A robust E learning recommendation system based on novel interval valued bipolar fuzzy hypersoft set theory. [PDF]
Sci RepHarl MI +4 more
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A decision-theoretic framework for wastewater treatment performance assessment based on a fuzzy parameterized fuzzy hypersoft set approach. [PDF]
Sci RepSaeed MH +4 more
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A Framework for Susceptibility Analysis of Brain Tumours Based on Uncertain Analytical Cum Algorithmic Modeling. [PDF]
Bioengineering (Basel), 2023 Ur Rahman A +7 more
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An MCDM approach on Einstein aggregation operators under Bipolar Linear Diophantine Fuzzy Hypersoft Set. [PDF]
HeliyonNithya Sri S +5 more
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