{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2023,12,15]],"date-time":"2023-12-15T00:41:54Z","timestamp":1702600914420},"reference-count":0,"publisher":"IOS Press","isbn-type":[{"value":"9781643684703","type":"print"},{"value":"9781643684710","type":"electronic"}],"license":[{"start":{"date-parts":[[2023,12,12]],"date-time":"2023-12-12T00:00:00Z","timestamp":1702339200000},"content-version":"unspecified","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by-nc\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2023,12,12]]},"abstract":"<jats:p>As an extension of fuzzy sets, the interval-valued q-rung orthopair fuzzy sets (IVq-ROFSs) is a powerful tool for dealing with uncertainty problems. Furthermore, fuzzy entropy is a crucial indicator to measure the fuzzy degree of fuzzy sets. However, the current fuzzy entropy of IVq-ROFSs have some disadvantages. First, for some interval-valued q-rung orthopair fuzzy numbers (IVq-ROFNs), the existing fuzzy entropy cannot accurately measure the fuzzy degree. Second, it is not a reasonable method to utilize exact values as fuzzy entropy in the form of interval values. In this paper, the fuzzy entropy of IVq-ROFSs is characterized by interval values. The axiomatic definitions of IVq-ROFSs fuzzy entropy is given. Strict mathematical proof and a numerical example verify that the proposed axiomatic definition of fuzzy entropy is complete and avoids the loss of interval-valued fuzzy information.<\/jats:p>","DOI":"10.3233\/faia231069","type":"book-chapter","created":{"date-parts":[[2023,12,14]],"date-time":"2023-12-14T15:09:36Z","timestamp":1702566576000},"source":"Crossref","is-referenced-by-count":0,"title":["A New Interval-Valued Fuzzy Entropy Based on Interval-Valued Q-Rung Orthopair Fuzzy Sets"],"prefix":"10.3233","author":[{"given":"Yan","family":"Zheng","sequence":"first","affiliation":[{"name":"College of Computer Science and Engineering, Northwest Normal University, Lanzhou, 730070, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Hongwu","family":"Qin","sequence":"additional","affiliation":[{"name":"College of Computer Science and Engineering, Northwest Normal University, Lanzhou, 730070, China"},{"name":"Institute for Big Data Analytics and Artificial Intelligence (IBDAAI), Universiti Teknologi MARA, 40450, Shah Alam, Selangor, Malaysia"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Xiuqin","family":"Ma","sequence":"additional","affiliation":[{"name":"College of Computer Science and Engineering, Northwest Normal University, Lanzhou, 730070, China"},{"name":"Institute for Big Data Analytics and Artificial Intelligence (IBDAAI), Universiti Teknologi MARA, 40450, Shah Alam, Selangor, Malaysia"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Yibo","family":"Wang","sequence":"additional","affiliation":[{"name":"College of Computer Science and Engineering, Northwest Normal University, Lanzhou, 730070, China"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"7437","container-title":["Frontiers in Artificial Intelligence and Applications","Fuzzy Systems and Data Mining IX"],"original-title":[],"link":[{"URL":"https:\/\/ebooks.iospress.nl\/pdf\/doi\/10.3233\/FAIA231069","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2023,12,14]],"date-time":"2023-12-14T15:09:38Z","timestamp":1702566578000},"score":1,"resource":{"primary":{"URL":"https:\/\/ebooks.iospress.nl\/doi\/10.3233\/FAIA231069"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2023,12,12]]},"ISBN":["9781643684703","9781643684710"],"references-count":0,"URL":"https:\/\/doi.org\/10.3233\/faia231069","relation":{},"ISSN":["0922-6389","1879-8314"],"issn-type":[{"value":"0922-6389","type":"print"},{"value":"1879-8314","type":"electronic"}],"subject":[],"published":{"date-parts":[[2023,12,12]]}}}