{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,5,2]],"date-time":"2026-05-02T07:00:11Z","timestamp":1777705211302,"version":"3.51.4"},"reference-count":34,"publisher":"SAGE Publications","issue":"3","content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["IFS"],"published-print":{"date-parts":[[2021,3,2]]},"abstract":"<jats:p>A scenario that often encounters in the event of aggregating options of different experts for the acquisition of a robust overall consensus is the possible existence of extremely large or small values termed as outliers in this paper, which easily lead to counter-intuitive results in decision aggregation. This paper attempts to devise a novel approach to tackle the consensus outliers especially for non-uniform data, filling the gap in the existing literature. In particular, the concentrate region for a set of non-uniform data is first computed with the proposed searching algorithm such that the domain of aggregation function is partitioned into sub-regions. The aggregation will then operate adaptively with respect to the corresponding sub-regions previously partitioned. Finally, the overall aggregation is operated with a proposed novel consensus measure. To demonstrate the working and efficacy of the proposed approach, several illustrative examples are given in comparison to a number of alternative aggregation functions, with the results achieved being more intuitive and of higher consensus.<\/jats:p>","DOI":"10.3233\/jifs-200278","type":"journal-article","created":{"date-parts":[[2021,1,5]],"date-time":"2021-01-05T18:03:09Z","timestamp":1609869789000},"page":"3999-4012","source":"Crossref","is-referenced-by-count":2,"title":["Mixed aggregation functions for outliers detection"],"prefix":"10.1177","volume":"40","author":[{"given":"Hengshan","family":"Zhang","sequence":"first","affiliation":[{"name":"The School of Computer Science and Technology, Xi\u2019an University of Posts and Telecommunications, Xi\u2019an, Shaanxi, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Chunru","family":"Chen","sequence":"additional","affiliation":[{"name":"The School of Computer Science and Technology, Xi\u2019an University of 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