Personnel appointments: a pythagorean fuzzy sets approach using similarity measure
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@Article{JICS-14-094,
author = {Paul Augustine Ejegwa},
title = {Personnel appointments: a pythagorean fuzzy sets approach using similarity measure},
journal = {Journal of Information and Computing Science},
year = {2024},
volume = {14},
number = {2},
pages = {094--102},
abstract = { This paper explores the advantage of Pythagorean fuzzy sets in personnel appointments by
employing normalized Euclidean similarity to find the similarity between applicants to each positions. The
choice of Euclidean similarity for Pythagorean fuzzy sets by incorporating the three traditional parameters, is
because it gives a reliable similarity with respect to other similarity measures for Pythagorean fuzzy sets that
incorporate the three traditional parameters as studied in literature. By finding the similarity of the applicants
and positions (both in Pythagorean fuzzy pairs/values), in the light of the qualifications require by the
organisation, we determine the suitable applicants for the available positions. Also, we propose the notions of
level sets of Pythagorean fuzzy sets and Pythagorean fuzzy pairs.
},
issn = {1746-7659},
doi = {https://doi.org/},
url = {http://global-sci.org/intro/article_detail/jics/22419.html}
}
TY - JOUR
T1 - Personnel appointments: a pythagorean fuzzy sets approach using similarity measure
AU - Paul Augustine Ejegwa
JO - Journal of Information and Computing Science
VL - 2
SP - 094
EP - 102
PY - 2024
DA - 2024/01
SN - 14
DO - http://doi.org/
UR - https://global-sci.org/intro/article_detail/jics/22419.html
KW - Fuzzy set, Intuitionistic fuzzy set, Personnel appointments, Pythagorean fuzzy pairs,
Pythagorean fuzzy set, Similarity measure
AB - This paper explores the advantage of Pythagorean fuzzy sets in personnel appointments by
employing normalized Euclidean similarity to find the similarity between applicants to each positions. The
choice of Euclidean similarity for Pythagorean fuzzy sets by incorporating the three traditional parameters, is
because it gives a reliable similarity with respect to other similarity measures for Pythagorean fuzzy sets that
incorporate the three traditional parameters as studied in literature. By finding the similarity of the applicants
and positions (both in Pythagorean fuzzy pairs/values), in the light of the qualifications require by the
organisation, we determine the suitable applicants for the available positions. Also, we propose the notions of
level sets of Pythagorean fuzzy sets and Pythagorean fuzzy pairs.
Paul Augustine Ejegwa. (2024). Personnel appointments: a pythagorean fuzzy sets approach using similarity measure.
Journal of Information and Computing Science. 14 (2).
094-102.
doi:
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