Noor Rehman

Orcid: 0000-0003-3094-4865

According to our database1, Noor Rehman authored at least 29 papers between 2014 and 2023.

Collaborative distances:
  • Dijkstra number2 of four.
  • Erdős number3 of five.

Timeline

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Bibliography

2023
A new class of fuzzy implications derived from non associative structures and its characterizations.
J. Intell. Fuzzy Syst., 2023

Another view on tolerance based multigranulation <i>q</i>-rung orthopair fuzzy rough sets with applications.
J. Intell. Fuzzy Syst., 2023

Generalized fuzzy rough sets based on (β, δ)-fuzzy similarity relation and their application to emergency management.
J. Ambient Intell. Humaniz. Comput., 2023

q-Rung Orthopair Probabilistic Hesitant Fuzzy Rough Aggregation Information and Their Application in Decision Making.
Int. J. Fuzzy Syst., 2023

Decision-Making Techniques Based on q-Rung Orthopair Probabilistic Hesitant Fuzzy Information: Application in Supply Chain Financing.
Complex., 2023

2022
A Decision-Making Framework Using q-Rung Orthopair Probabilistic Hesitant Fuzzy Rough Aggregation Information for the Drug Selection to Treat COVID-19.
Complex., 2022

2021
Generalized multigranulation fuzzy rough sets based on upward additive consistency.
Soft Comput., 2021

Evaluation of the product quality of the online shopping platform using <i>t</i>-spherical fuzzy preference relations.
J. Intell. Fuzzy Syst., 2021

A comprehensive study of upward fuzzy preference relation based fuzzy rough set models: Properties and applications in treatment of coronavirus disease.
Int. J. Intell. Syst., 2021

Note on "Tolerance-based intuitionistic fuzzy-rough set approach for attribute reduction".
Expert Syst. Appl., 2021

q-Rung Orthopair Fuzzy Rough Einstein Aggregation Information-Based EDAS Method: Applications in Robotic Agrifarming.
Comput. Intell. Neurosci., 2021

2020
Note on "Fuzzy multi-granulation decision-theoretic rough sets based on fuzzy preference relation".
Soft Comput., 2020

Uncertainty measure of <i>Z</i>-soft covering rough models based on a knowledge granulation.
J. Intell. Fuzzy Syst., 2020

Labor-management negotiation conflict analysis based on soft preference relation.
J. Intell. Fuzzy Syst., 2020

Soft ordered based multi-granulation rough sets and incomplete information system.
J. Intell. Fuzzy Syst., 2020

Another View on Intuitionistic Fuzzy Preference Relation-Based Aggregation Operators and Their Applications.
Int. J. Fuzzy Syst., 2020

Soft dominance based multigranulation decision theoretic rough sets and their applications in conflict problems.
Artif. Intell. Rev., 2020

2019
Variable precision multi decision λ-soft dominance based rough sets and their applications in conflict problems.
J. Intell. Fuzzy Syst., 2019

Medicines selection via fuzzy upward β-covering rough sets.
J. Intell. Fuzzy Syst., 2019

Soft ordered approximations and incomplete information system.
J. Intell. Fuzzy Syst., 2019

Soft dominance based rough sets with applications in information systems.
Int. J. Approx. Reason., 2019

Multi-Granulation Fuzzy Rough Sets Based on Fuzzy Preference Relations and Their Applications.
IEEE Access, 2019

2018
Another Approach to Roughness of Soft Graphs with Applications in Decision Making.
Symmetry, 2018

Z-soft rough fuzzy graphs: A new approach to decision making.
J. Intell. Fuzzy Syst., 2018

New types of dominance based multi-granulation rough sets and their applications in Conflict analysis problems.
J. Intell. Fuzzy Syst., 2018

A more efficient conflict analysis based on soft preference relation.
J. Intell. Fuzzy Syst., 2018

Pathogens constancy, harbinger of nosocomial infection cum identification of resistant genes and drug designing.
Comput. Biol. Chem., 2018

SDMGRS: Soft Dominance Based Multi Granulation Rough Sets and Their Applications in Conflict Analysis Problems.
IEEE Access, 2018

2014
Some characterizations of ternary semigroups by the properties of their (∈<sub>γ</sub>, ∈<sub>>γ</sub>⋁q<sub>>δ</sub>)-fuzzy ideals.
J. Intell. Fuzzy Syst., 2014


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