Visualization of two-dimensional interval type-2 fuzzy membership functions using general type-2 fuzzy membership functions
DC Field | Value | Language |
---|---|---|
dc.contributor.author | Chourasia, Rishav | - |
dc.contributor.author | Saxena, Vaibhav | - |
dc.contributor.author | Yadala, Nikhil | - |
dc.contributor.author | Rhee, Frank chung hoon | - |
dc.date.accessioned | 2021-06-22T15:24:41Z | - |
dc.date.available | 2021-06-22T15:24:41Z | - |
dc.date.created | 2021-01-22 | - |
dc.date.issued | 2017-06 | - |
dc.identifier.uri | https://scholarworks.bwise.kr/erica/handle/2021.sw.erica/11687 | - |
dc.description.abstract | In this paper, we propose a novel method for visualizing two-dimensional interval type-2 fuzzy membership functions (2-D IT2 FMFs) using one-dimensional general type-2 fuzzy membership functions (1-D GT2 FMFs), and also describe the procedure for extending our method to fuzzy sets representing higher dimensional data. Then we present a type reduction method for mapping 2-D IT2 fuzzy sets into 2-D type-1 fuzzy sets that uses alpha-plane representation of general fuzzy sets. We discuss the problem of 'multiple membership values for the same element,' which violates set properties, in an IT2 Fuzzy C-means (FCM) algorithm for clustering and propose a solution that uses transformations in the visualization method. These techniques can be applied to applications involving fuzzy sets that represent multidimensional data for proper visualization and type reduction, such as image segmentation, classification and prediction, to name a few. © 2017 IEEE. | - |
dc.language | 영어 | - |
dc.language.iso | en | - |
dc.publisher | Institute of Electrical and Electronics Engineers Inc. | - |
dc.title | Visualization of two-dimensional interval type-2 fuzzy membership functions using general type-2 fuzzy membership functions | - |
dc.type | Article | - |
dc.contributor.affiliatedAuthor | Rhee, Frank chung hoon | - |
dc.identifier.doi | 10.1109/IFSA-SCIS.2017.8023274 | - |
dc.identifier.scopusid | 2-s2.0-85030838481 | - |
dc.identifier.wosid | 000427063700056 | - |
dc.identifier.bibliographicCitation | IFSA-SCIS 2017 - Joint 17th World Congress of International Fuzzy Systems Association and 9th International Conference on Soft Computing and Intelligent Systems, pp.1 - 5 | - |
dc.relation.isPartOf | IFSA-SCIS 2017 - Joint 17th World Congress of International Fuzzy Systems Association and 9th International Conference on Soft Computing and Intelligent Systems | - |
dc.citation.title | IFSA-SCIS 2017 - Joint 17th World Congress of International Fuzzy Systems Association and 9th International Conference on Soft Computing and Intelligent Systems | - |
dc.citation.startPage | 1 | - |
dc.citation.endPage | 5 | - |
dc.type.rims | ART | - |
dc.type.docType | Conference Paper | - |
dc.description.journalClass | 1 | - |
dc.description.isOpenAccess | N | - |
dc.description.journalRegisteredClass | scie | - |
dc.description.journalRegisteredClass | scopus | - |
dc.relation.journalResearchArea | Computer Science | - |
dc.relation.journalWebOfScienceCategory | Computer Science, Artificial Intelligence | - |
dc.relation.journalWebOfScienceCategory | Computer Science, Theory & Methods | - |
dc.subject.keywordPlus | REDUCTION | - |
dc.subject.keywordAuthor | Interval type-2 fuzzy sets | - |
dc.subject.keywordAuthor | general type-2 fuzzy sets | - |
dc.subject.keywordAuthor | two-dimensional type-2 fuzzy sets | - |
dc.subject.keywordAuthor | footprint of uncertainty | - |
dc.subject.keywordAuthor | type reduction | - |
dc.subject.keywordAuthor | fuzzy C-means clustering | - |
dc.identifier.url | https://ieeexplore.ieee.org/document/8023274/ | - |
Items in ScholarWorks are protected by copyright, with all rights reserved, unless otherwise indicated.
55 Hanyangdeahak-ro, Sangnok-gu, Ansan, Gyeonggi-do, 15588, Korea+82-31-400-4269 sweetbrain@hanyang.ac.kr
COPYRIGHT © 2021 HANYANG UNIVERSITY. ALL RIGHTS RESERVED.
Certain data included herein are derived from the © Web of Science of Clarivate Analytics. All rights reserved.
You may not copy or re-distribute this material in whole or in part without the prior written consent of Clarivate Analytics.