Method of least squares applied to the generalized modus ponens with interval-valued fuzzy sets
Firstly we present a geometric interpretation of interval-valued fuzzy sets. Secondly, we apply the method of least squares to the fuzzy inference rules when working with these sets. We begin approximating the lower and upper extremes of the membership intervals to axb type functions by means of the...
| Autores: | , , |
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| Tipo de recurso: | artículo |
| Fecha de publicación: | 1999 |
| País: | España |
| Institución: | Universitat Politècnica de Catalunya (UPC) |
| Repositorio: | UPCommons. Portal del coneixement obert de la UPC |
| Idioma: | inglés |
| OAI Identifier: | oai:upcommons.upc.edu:2099/3558 |
| Acceso en línea: | https://hdl.handle.net/2099/3558 |
| Access Level: | acceso abierto |
| Palabra clave: | Approximate reasoning Fuzzy inference rules Generalized modus ponens Interval-valued fuzzy set Method of least squares Intel·ligència artificial Classificació AMS::68 Computer science::68T Artificial intelligence |
| Sumario: | Firstly we present a geometric interpretation of interval-valued fuzzy sets. Secondly, we apply the method of least squares to the fuzzy inference rules when working with these sets. We begin approximating the lower and upper extremes of the membership intervals to axb type functions by means of the method of least squares. Then we analyze a technique for evaluating the conclusion of the generalized modus ponens and we verify the fulfillment of Fukami and alumni axioms [9]. |
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