During the few last years, several successful approaches for the integration of soft computing techniques have been proposed in the area of data-driven fuzzy modeling (DDFM). However, there is a lack of methodological and general purpose hybridization in an easy and unified manner. This work outlines the design of a new DDFM framework called METHOD, offering the functionalities needed to combine techniques into hybrid strategies for DDFM tasks. Bearing in mind our main goal, a previous analysis of several existing DDFM techniques helps us: (1) to identify the most usual interaction schemes, by means of which methods are combined into DDFM hybrid strategies; (2) to exemplify requirements and effects for different techniques determining suitable combinations; and (3) to establish the universe of discourse based on which of these requirements and effect are defined. All these ideas are illustrated with examples.
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Valdés-Vela et al. (2004) studied this question.
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