Similarity-based method for reduction of fuzzy rules
Abstract:
Fuzzy Similarity Measures (FSMs) are widely used for comparison of fuzzy sets, as well as fuzzy rules. A multitude of different FSMs have been proposed so far. It is not straightforward to identify a single FSM that is the most suitable for a given task. In this paper, we investigate suitability of a few FSMs for the problem of reduction of number of rules for an image segmentation process. We use Dirichlet-based approach to generate fuzzy sets that are further used for construction of fuzzy if-then rules. We analyze similarity of these rules and select a specified number of rules for image segmentation purposes. We applied this approach to two different images.
Año de publicación:
2016
Keywords:
Fuente:
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Tipo de documento:
Conference Object
Estado:
Acceso restringido
Áreas de conocimiento:
- Inteligencia artificial
- Lógica difusa
Áreas temáticas:
- Métodos informáticos especiales
- Gramática del inglés estándar
- Probabilidades y matemática aplicada