Similarity Measures of Spherical Fuzzy Sets Based on Cosine Function and Their Applications
In this paper, we defined ten similarity measures between spherical fuzzy sets (SFSs) based on the cosine function by considering the degree of positive-membership, degree of neutral-membership, degree of non-membership and degree of refusual-membership in SFSs. Then, we applied these similarity mea...
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Format: | Article |
Language: | English |
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IEEE
2019-01-01
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Series: | IEEE Access |
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Online Access: | https://ieeexplore.ieee.org/document/8882324/ |
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author | Guiwu Wei Jie Wang Mao Lu Jiang Wu Cun Wei |
author_facet | Guiwu Wei Jie Wang Mao Lu Jiang Wu Cun Wei |
author_sort | Guiwu Wei |
collection | DOAJ |
description | In this paper, we defined ten similarity measures between spherical fuzzy sets (SFSs) based on the cosine function by considering the degree of positive-membership, degree of neutral-membership, degree of non-membership and degree of refusual-membership in SFSs. Then, we applied these similarity measures and weighted similarity measures between SFSs to pattern recognition and medical diagnosis. Finally, two illustrative examples are designed to show the efficiency of the similarity measures for pattern recognition and medical diagnosis. |
first_indexed | 2024-04-12T05:01:04Z |
format | Article |
id | doaj.art-20c8b73d843b4706894bfaa7fe580e1d |
institution | Directory Open Access Journal |
issn | 2169-3536 |
language | English |
last_indexed | 2024-04-12T05:01:04Z |
publishDate | 2019-01-01 |
publisher | IEEE |
record_format | Article |
series | IEEE Access |
spelling | doaj.art-20c8b73d843b4706894bfaa7fe580e1d2022-12-22T03:46:59ZengIEEEIEEE Access2169-35362019-01-01715906915908010.1109/ACCESS.2019.29492968882324Similarity Measures of Spherical Fuzzy Sets Based on Cosine Function and Their ApplicationsGuiwu Wei0https://orcid.org/0000-0001-9074-2005Jie Wang1https://orcid.org/0000-0001-6286-9893Mao Lu2Jiang Wu3Cun Wei4https://orcid.org/0000-0002-6195-8699School of Business, Sichuan Normal University, Chengdu, ChinaSchool of Business, Sichuan Normal University, Chengdu, ChinaSchool of Business, Sichuan Normal University, Chengdu, ChinaSchool of Statistics, Southwestern University of Finance and Economics, Chengdu, ChinaSchool of Statistics, Southwestern University of Finance and Economics, Chengdu, ChinaIn this paper, we defined ten similarity measures between spherical fuzzy sets (SFSs) based on the cosine function by considering the degree of positive-membership, degree of neutral-membership, degree of non-membership and degree of refusual-membership in SFSs. Then, we applied these similarity measures and weighted similarity measures between SFSs to pattern recognition and medical diagnosis. Finally, two illustrative examples are designed to show the efficiency of the similarity measures for pattern recognition and medical diagnosis.https://ieeexplore.ieee.org/document/8882324/Spherical fuzzy sets (SFSs)cosine functioncosine similarity measurepattern recognitionmedical diagnosis |
spellingShingle | Guiwu Wei Jie Wang Mao Lu Jiang Wu Cun Wei Similarity Measures of Spherical Fuzzy Sets Based on Cosine Function and Their Applications IEEE Access Spherical fuzzy sets (SFSs) cosine function cosine similarity measure pattern recognition medical diagnosis |
title | Similarity Measures of Spherical Fuzzy Sets Based on Cosine Function and Their Applications |
title_full | Similarity Measures of Spherical Fuzzy Sets Based on Cosine Function and Their Applications |
title_fullStr | Similarity Measures of Spherical Fuzzy Sets Based on Cosine Function and Their Applications |
title_full_unstemmed | Similarity Measures of Spherical Fuzzy Sets Based on Cosine Function and Their Applications |
title_short | Similarity Measures of Spherical Fuzzy Sets Based on Cosine Function and Their Applications |
title_sort | similarity measures of spherical fuzzy sets based on cosine function and their applications |
topic | Spherical fuzzy sets (SFSs) cosine function cosine similarity measure pattern recognition medical diagnosis |
url | https://ieeexplore.ieee.org/document/8882324/ |
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