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:

    scopusscopus

    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