0564675 20230321162417.620221129235959.9 85140292178 000880093300017 10.1016/j.knosys.2022.109963 22 s. P cav_un_epca*02571730950-7051258Elsevier (a,b)-Aggregation functions (a,b)-Fusion functions n-Dimensional overlap functions t-conorms t-norms Uninorms cav_un_auth*0434043 Asmus T. C. BR K cav_un_auth*0330394 Sanz J. A. ES cav_un_auth*0330395 Dimuro G. P. BR cav_un_auth*0275658 Fernandez J. ES cav_un_auth*0101163 Mesiar Radko UTIA-B Ekonometrie Department of Econometrics E E Department of Econometrics 20 Ústav teorie informace a automatizace AV ČR, v. v. i. cav_un_auth*0271524 Bustince H. ES http://library.utia.cas.cz/separaty/2022/E/mesiar-0564675.pdf https://www.sciencedirect.com/science/article/pii/S0950705122010565?via%3Dihub An important problem faced when dealing with imperfect information in fusion processes the uncer-tainty regarding values of the membership degrees to be employed in fuzzy modeling. In this scenario, one can apply interval-valued (iv) fuzzy sets, in which the membership degrees are represented by intervals. A recurrent issue is the situation in which the quality of information carried by the intervals, expressed by their widths, suffers degradation during the fusion process. So, the main objective of this paper is to develop a general framework to construct iv-fusion functions whose outputs conserve the information quality of the operated intervals. To achieve that, first, extend important concepts such as width-limiting functions and width-limited iv-functions to the n-dimensional context. Then, we present a characterization for any subclass of increasing fusion function by their set of properties, followed by the interval extension of such characterization to obtain classes of width-limited iv-fusion functions. We show that our methodology is general enough to retrieve several classes of iv-aggregation functions from the literature. Two approaches for constructing width-limited iv-fusion functions are also presented, which enables the application of different subclasses of width-limited iv-fusion functions in fusion/aggregation processes with imperfect information. Finally, we present a case study on a classification problem. Specifically, we use IVTURS, a state-of-the-art iv-fuzzy rule-based classification system, and a particular subclass of width-limited iv-fusion functions (n-dimensional width-limited iv-overlap functions), showing that the control of the information quality through width limitation significantly enhances the accuracy of the classifier. WOS BA 10000 10200 10201 2023 6 RVO:67985556 https://hdl.handle.net/11104/0337894 S 109963 3+4 Article Computer Science Artificial Intelligence C COMPUTERSCIENCE.ARTIFICIALINTELLIGENCE 8.6 1.7 3.4 0.03615 1.443 36687 2.065 7.700 1246 Q1 87.2 Q2 Q1 1.5 Q1 87.2 2022 85140292178 SCOPUS PUBMED 000880093300017 WOS cav_un_epca*0257173 Knowledge-Based System 0950-7051 1872-7409 Roč. 258 č. 1 2022 Elsevier