Artificial Neural Network Dual Hesitant Fermatean Fuzzy Implementation in Transportation of COVID-19 Vaccine
Journal of Organizational and End User Computing
; 35(2):1-23, 2023.
Article
in English
| ProQuest Central | ID: covidwho-2294227
ABSTRACT
This article, in order to address impreciseness, initiated the notion of dual hesitant fermatean fuzzy sets (DHFFSs), as a generalization of the combination of dual hesitant fuzzy set (DHFS), dual hesitant Pythagorean fuzzy set (DHPFS) and Fermatean fuzzy set (FFS). The authors defined the fundamental set of operations for DHFFS. Additionally, the authors have also proposed two ranking functions and an accuracy function for the ordering of this novel set. In order to facilitate the pragmatic implementation of DHFFS in optimization, the authors formulated three types of transportation problem with dual hesitant Fermatean fuzzy (DHFF) parameters. To optimize the DHFF-TP, an algorithm was proposed with the help of one of the proposed ranking functions. Artificial neural network is also applied to the transportation problems in DHFF environment. A numerical example based on the transportation of COVID-19 vaccine with DHFF cost has also been carried out to validate out to validate our technique.
Computers--Electronic Data Processing; Artificial Neural Network; Dual Hesitant Fermatean Fuzzy Set; Dual Hesitant Fermatean Fuzzy Transportation Problem; Transportation problem; Algorithms; COVID-19 vaccines; Fuzzy sets; Ranking; Coronaviruses; Artificial neural networks; Neural networks; Optimization; Transportation networks; Vaccines
Full text:
Available
Collection:
Databases of international organizations
Database:
ProQuest Central
Topics:
Vaccines
Language:
English
Journal:
Journal of Organizational and End User Computing
Year:
2023
Document Type:
Article
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