@article{Alrasheedi2023, 
author = {Adel Fahad Alrasheedi and Jungeun Kim and Rukhsana Kausar},
title = {q-Rung orthopair fuzzy information aggregation and their application towards material selection},
year = {2023},
journal = {AIMS Mathematics},
volume = {8},
number = {8},
pages = {18780-18808},
keywords = {decision-making, aggregation operators, soft-max function, q-rung orthopair fuzzy number},
url = {https://www.sciopen.com/article/10.3934/math.2023956},
doi = {10.3934/math.2023956},
abstract = {Material selection is a complex process that involves selecting the best material for a given application. It is a critical process in engineering, and the importance of selecting the right material for the job cannot be overstated. Multi-criteria decision-making (MCDM) is an important tool that can be used to help engineers make informed decisions about material selection. The logistic function can be extended using the soft-max function, which is widely used in stochastic classification methods like neural nets, soft-max extrapolation, linear differential analysis, and Naïve Bayes detectors. This has inspired researchers to develop soft-max-based fuzzy aggregation operators (AOs) for q-rung orthopair fuzzy sets (q-ROPFS) and to propose an MCDM approach based on these AOs. To test the effectiveness of this approach, the researchers applied it to a practical problem using q-rung orthopair fuzzy data and conducted a numerical example to validate the suggested procedures.}
}