caa a22 4500 605470294 CHVBK 20210128100327.0 cr unu---uuuuu 210128e20150801xx s 000 0 eng 10.1007/s00500-014-1398-2 doi (NATIONALLICENCE)springer-10.1007/s00500-014-1398-2 Introducing $$g$$ g -normal fuzzy relational models [Elektronische Daten] [Arya Aghili Ashtiani, Mohammad Menhaj] In this paper, a harmonious family of fuzzy relational models (FRMs) called $$g$$ g -normal FRMs is introduced. By selecting a value for the scalar parameter $$g$$ g , a member of this family is determined for which all parts of the model are configured accordingly. In this regard, a specific configuration for FRMs as well as an appropriate derivative-based iterative identification procedure are proposed. While preserving the high modeling capability of FRMs, the proposed model configuration along with the proposed identification algorithm alleviate both the lack of analyzability and the possible existence of hard conflicts between the rules in the rule-base. Furthermore, high relative errors in output computations are prevented using the proposed scheme. The modeling scheme is applied finally to the Box-Jenkins gas furnace benchmark problem as well as a new classification problem. The results are verified by simulation. Springer-Verlag Berlin Heidelberg, 2014 Fuzzy systems nationallicence Fuzzy relational matrix (FRX) nationallicence Fuzzy relational inner composition (FRIC) nationallicence Yager t -conorm nationallicence Model configuration nationallicence Aghili Ashtiani Arya Department of Electrical Engineering, Amirkabir University of Technology, Hafez Ave., P. O. Box 15914, Tehran, Iran aut Menhaj Mohammad Department of Electrical Engineering, Amirkabir University of Technology, Hafez Ave., P. O. Box 15914, Tehran, Iran aut Soft Computing Springer Berlin Heidelberg 19/8(2015-08-01), 2163-2171 1432-7643 19:8<2163 2015 19 500 https://doi.org/10.1007/s00500-014-1398-2 text/html Onlinezugriff via DOI BK010053 XK010053 XK010000 Metadata rights reserved Springer special CC-BY-NC licence nationallicence 1 research-article jats NATIONALLICENCE NATIONALLICENCE NL-springer NATIONALLICENCE 856 40 https://doi.org/10.1007/s00500-014-1398-2 text/html Onlinezugriff via DOI NATIONALLICENCE 700 1- Aghili Ashtiani Arya Department of Electrical Engineering, Amirkabir University of Technology, Hafez Ave., P. O. Box 15914, Tehran, Iran aut NATIONALLICENCE 700 1- Menhaj Mohammad Department of Electrical Engineering, Amirkabir University of Technology, Hafez Ave., P. O. Box 15914, Tehran, Iran aut NATIONALLICENCE 773 0- Soft Computing Springer Berlin Heidelberg 19/8(2015-08-01), 2163-2171 1432-7643 19:8<2163 2015 19 500