Composition of interval-valued fuzzy relations using aggregation functions
| Autor: | Barbara Pekala, Mikel Galar, Mikel Elkano, Urszula Bentkowska, Humberto Bustince, José Antonio Sanz |
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| Rok vydání: | 2016 |
| Předmět: |
0209 industrial biotechnology
Information Systems and Management Fuzzy classification Fuzzy set 02 engineering and technology Type-2 fuzzy sets and systems Defuzzification Computer Science Applications Theoretical Computer Science Algebra 020901 industrial engineering & automation Artificial Intelligence Control and Systems Engineering Fuzzy mathematics 0202 electrical engineering electronic engineering information engineering Fuzzy set operations Fuzzy number 020201 artificial intelligence & image processing Algorithm Software Membership function Mathematics |
| Zdroj: | Information Sciences. 369:690-703 |
| ISSN: | 0020-0255 |
| DOI: | 10.1016/j.ins.2016.07.048 |
| Popis: | We study interval-valued fuzzy relations for the Generalized Modus Ponens.We study the composition of these relations using interval aggregation functions.We study the properties of these compositions.We develop an inference method using interval-valued fuzzy relations.We present an illustrative example. In this paper we present the composition of interval-valued fuzzy relations using interval-valued aggregation functions. In particular, we propose a generalization of Zadeh's composition rule, replacing the minimum by an interval-valued aggregation function. We analyze the preservation of different properties of interval-valued fuzzy relations by this new composition, and we include an illustrative example in approximate reasoning in order to justify our proposal. |
| Databáze: | OpenAIRE |
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