dc.contributor.author |
Kouatli, Issam |
|
dc.date.accessioned |
2019-03-11T12:27:27Z |
|
dc.date.available |
2019-03-11T12:27:27Z |
|
dc.date.copyright |
2018 |
en_US |
dc.date.issued |
2019-03-11 |
|
dc.identifier.issn |
1064-1246 |
en_US |
dc.identifier.uri |
http://hdl.handle.net/10725/10171 |
en_US |
dc.description.abstract |
Employee performance evaluations are one type of decision-making process that is embedded with uncertainty and ambiguity before concluding the final index. After reviewing different approaches to achieving such target, this paper introduces the implementation of fuzzification mechanism termed as “Fuzzimetric Sets” as a method of defining the minimum and maximum tolerance possibilities within pre-defined fuzzy sets. Decision-making evaluation process would be dependent on the inferred minimum to maximum defuzzified differences (spectrum). Based on this concept, a prototype was built to measure the employee performance level allowing much more flexibility when taking a decision under uncertainty. This application was termed as “Fuzzimetric Employee Evaluation System” (FEES). Comparative study of FEES was done by comparing the results of the work of another researcher investigated the same field of Fuzzy-employee-evaluation |
en_US |
dc.language.iso |
en |
en_US |
dc.title |
Fuzzimetric employee evaluations system (FEES) |
en_US |
dc.type |
Article |
en_US |
dc.description.version |
Published |
en_US |
dc.title.subtitle |
A multivariable-modular approach |
en_US |
dc.author.school |
SOB |
en_US |
dc.author.idnumber |
200301034 |
en_US |
dc.author.department |
Information Technology And Operations Management |
en_US |
dc.description.embargo |
N/A |
en_US |
dc.relation.journal |
Journal of Intelligent & Fuzzy Systems |
en_US |
dc.journal.volume |
35 |
en_US |
dc.journal.issue |
4 |
en_US |
dc.article.pages |
4717-4729 |
en_US |
dc.keywords |
Fuzzy sets |
en_US |
dc.keywords |
Employee performance systems |
en_US |
dc.keywords |
Fuzzimetric arcs |
en_US |
dc.keywords |
fuzzy inference modular approach |
en_US |
dc.identifier.doi |
http://dx.doi.org/10.3233/JIFS-181202 |
en_US |
dc.identifier.ctation |
Kouatli, I. (2018). Fuzzimetric employee evaluations system (FEES): A multivariable-modular approach. Journal of Intelligent & Fuzzy Systems, 35(4), 4717-4729. |
en_US |
dc.author.email |
issam.kouatli@lau.edu.lb |
en_US |
dc.identifier.tou |
http://libraries.lau.edu.lb/research/laur/terms-of-use/articles.php |
en_US |
dc.identifier.url |
https://content.iospress.com/articles/journal-of-intelligent-and-fuzzy-systems/ifs181202 |
en_US |
dc.author.affiliation |
Lebanese American University |
en_US |