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Syst."],"published-print":{"date-parts":[[2023,6]]},"abstract":"<jats:title>Abstract<\/jats:title><jats:p>As a more massive feasible and prominent tool than the complex interval-valued Pythagorean fuzzy (CIVPF) set and complex interval-valued intuitionistic fuzzy (CIVIF) set, the complex interval-valued q-rung orthopair fuzzy (CIVQROF) set has been usually used to represent ambiguity and vagueness for real-life decision-making problems. In this paper, we firstly proposed some distance measures, Yager operational laws, and their comparison method. Further, we developed CIVQROF Yager weighted averaging (CIVQROFYWA), CIVQROF Yager ordered weighted averaging (CIVQROFYOWA), CIVQROF Yager weighted geometric (CIVQROFYWG), CIVQROF Yager ordered weighted geometric (CIVQROFYOWG) operators with CIVQROF information, and some certain well-known and feasible properties and outstanding results are explored in detail. Moreover, we proposed a new and valuable technique for handling multi-attribute decision-making problems with CIVQROF information. Lastly, a practical evaluation regarding the high blood pressure diseases of the patient is evaluated to illustrate the feasibility and worth of the proposed approaches.<\/jats:p>","DOI":"10.1007\/s40747-022-00901-8","type":"journal-article","created":{"date-parts":[[2022,11,29]],"date-time":"2022-11-29T08:04:52Z","timestamp":1669709092000},"page":"3185-3210","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":9,"title":["Yager aggregation operators based on complex interval-valued q-rung orthopair fuzzy information and their application in decision making"],"prefix":"10.1007","volume":"9","author":[{"given":"Xin","family":"Dong","sequence":"first","affiliation":[]},{"given":"Zeeshan","family":"Ali","sequence":"additional","affiliation":[]},{"given":"Tahir","family":"Mahmood","sequence":"additional","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0001-5048-8145","authenticated-orcid":false,"given":"Peide","family":"Liu","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2022,11,29]]},"reference":[{"issue":"1","key":"901_CR1","doi-asserted-by":"crossref","first-page":"820","DOI":"10.1016\/j.asoc.2007.06.006","volume":"8","author":"EI Papageorgiou","year":"2008","unstructured":"Papageorgiou EI, Spyridonos PP, Glotsos DT, Stylios CD, Ravazoula P, Nikiforidis GN, Groumpos PP (2008) Brain tumor characterization using the soft computing technique of fuzzy cognitive maps. 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