110 research outputs found

    Formal presentation of fuzzy systems with multiple sensor inputs

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    The paper addresses the problems of complexity in fuzzy rule based systems with multiple sensor inputs. The number of fuzzy rules in this case is an exponential function of the number of inputs. Some of the existing methods for rule base reductions are reviewed and their drawbacks summarized. As an alternative, a novel methodology for complexity management in fuzzy systems is presented which is based on formal presentation techniques such as integer tables. A Matlab example is shown illustrating the presentation of a fuzzy rule base with an integer table. Finally, some future research directions are outlined within the framework of the proposed methodology

    Advanced inference in fuzzy systems by rule base compression

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    This paper describes a method for rule base compression of fuzzy systems. The method compresses a fuzzy system with an arbitrarily large number of rules into a smaller fuzzy system by removing the redundancy in the fuzzy rule base. As a result of this compression, the number of on-line operations during the fuzzy inference process is significantly reduced without compromising the solution. This rule base compression method outperforms significantly other known methods for fuzzy rule base reduction.Peer Reviewe

    Collaborative decision making by ensemble rule based classification systems

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    Cognitive modelling of language acquisition with complex networks

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    ABSTRACT Cognitive modelling is a well-established computational intelligence tool, which is very useful for studying cognitive phenomena, such as young children's first language acquisition. Specifically, linguistic modelling has recently benefited greatly from complex network theory by modelling large sets of empirical linguistic data as complex networks, thereby illuminating interesting new patterns and trends. In this chapter, we show how simple network analysis techniques can be applied to the study of language acquisition, and we argue that they reveal otherwise hidden information. We also note that a key network parameter -the ranked frequency distribution of the links -provides useful knowledge about the data, even though it had been previously neglected in this domain
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