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In this paper, we propose a three-objective evolutionary algorithm to generate a set of Mamdani fuzzy rule-based systems (MFRBSs) with different tradeoffs between accuracy, rule base (RB) complexity and partition integrity. The RB, the linguistic partition granularities and the membership function (MF) parameters are concurrently learnt during the evolutionary process. In particular, the granularity...
When applied to high dimensional datasets, multi-objective evolutionary learning (MOEL) of fuzzy rule-based systems suffers from high computational costs, mainly due to the fitness evaluation. To use a reduced training set (TS) in place of the overall TS could considerably lessen the required effort. How this reduction should be performed, especially in the context of regression, is still an open...
This paper is focused on the design and development of an architecture that is able to provide remote segmentation service to various kinds of images or applications. The system exploits the functionalities offered by the already existing desktop application Isocontour by extending its capabilities toward a client-server environment. In order to achieve this goal, the original Isocontour code has...
The present work is focused on design and development of an architecture able to provide a remote segmentation service for various kinds of images or applications. The system exploits the functionalities offered by the already existing desktop application Isocontorni, by extending its capabilities towards client/server environment. In order to achieve this goal the original Isocontorni code has been...
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