A novel entropy of intuitionistic fuzzy sets based on similarity and its application in finance

Autor:	Duc Quynh Tran, Xuan Thao Nguyen, Doan Dong Nguyen, Quang Thuan Nguyen
Rok vydání:	2022
Předmět:	Statistics and Probability Artificial Intelligence General Engineering
Zdroj:	Journal of Intelligent & Fuzzy Systems. 43:3899-3909
ISSN:	1875-8967 1064-1246
DOI:	10.3233/jifs-211563
Popis:	In this paper, we propose a new formula for the entropy based on similarity measures of intuitionistic fuzzy sets (IFS). The contribution of this work is the proof that the new formula satisfies all the conditions of entropy. The experimentation on some examples shows that the new entropy is useful. Besides, we use the new entropy and similarity measures to design an algorithm for ranking assets in stock markets. The numerical results on 5 benchmark data sets were reported. It points out that the entropy and the similarity measures of IFS may provide an alternative tool for solving portfolio selection problems.
Databáze:	OpenAIRE
Externí odkaz:	https://explore.openaire.eu/search/publication?articleId=doi_________::f6b4884429f49d462f7937a10a0f75ef https://doi.org/10.3233/jifs-211563 Zobrazit plný text záznamu Plný text ve formátu PDF Plný text ve formátu HTML
Nepřihlášeným uživatelům se plný text nezobrazuje	K zobrazení výsledku je třeba se přihlásit.