
The notion of fuzzy subsets was introduced by L.A.Zadeh (1965) and it was generalised to intuitionistic fuzzy subsets by K.Atanassov [1]. After the invention of intuitionistic fuzzy subsets, many real life problems are studied accurately [7, 13, 14]. The measure of fuzziness was studied in [12, 16]. The ranking of intuitionistic fuzzy numbers plays a main role in modelling many real life problems involving intuitionistic fuzzy decision making, intuitionistic fuzzy clustering. H.B.Mitchell introduced a method of ranking intuitionistic fuzzy numbers in [10]. In this paper, a new method of intuitionistic fuzzy scoring to intuitionistic fuzzy numbers that generalizes Chen and Hwangpsilas scoring method for ranking of intuitionistic fuzzy numbers has been introduced and studied.
| selected citations These citations are derived from selected sources. This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | 19 | |
| popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network. | Top 10% | |
| influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | Top 10% | |
| impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network. | Average |
