Volume 8, Issue 3 (Journal of Control, V.8, N.3 Fall 2014)                   JoC 2014, 8(3): 27-49 | Back to browse issues page

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Abstract:   (5936 Views)
Interval knowledge is introduced in this paper. Interval knowledge is new paradigm for representation of human’s partial-implicit knowledge which applies granular information-based computational methods, e.g., fuzzy sets and rough sets. Interval-based intelligent systems and controllers are ones used interval knowledge and granular computing approaches. These systems and controllers are able to deal with types of vagueness and uncertainties. During past two decades, several researches have proved interval-based intelligent system are more capable than ones use traditional approaches in order to processes of data, especially in noisy situations. In this paper, rough sets theory, rough set neural networks, and theory of fuzzy type2 as most important interval knowledge approaches are presented, and also some their applications are summarized.
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Type of Article: Research paper | Subject: Special
Received: 2015/02/27 | Accepted: 2015/02/27 | Published: 2015/02/27