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Evolving fuzzy systems.

Research output: Contribution to journalJournal article


<mark>Journal publication date</mark>2008
Issue number2
Pages (from-to)6274
<mark>Original language</mark>English


Evolving fuzzy systems (EFS) can be defined as self-developing, self-learning fuzzy rule-based or neuro-fuzzy systems that have both their parameters but also (more importantly) their structure self-adapting on-line. They are usually associated with streaming data and on-line (often real-time) modes of operation. In a narrower sense they can be seen as adaptive fuzzy systems. The difference is that evolving fuzzy systems assume on-line adaptation of system structure in addition to the parameter adaptation which is usually associated with the term adaptive. They also allow for adaptation of the learning mechanism. Therefore, evolving assumes a higher level of adaptation. In this definition the English word evolving is used with its core meaning as described in the Oxford dictionary (Hornby, 1974; p.294), namely unfolding; developing; being developed, naturally and gradually. Often evolving is used in relation to so called evolutionary and genetic algorithms. The meaning of the term evolutionary is defined in the Oxford dictionary as development of more complicated forms of life (plants, animals) from earlier and simpler forms. EFS consider a gradual development of the underlying (fuzzy or neuro-fuzzy) system structure and do not deal with such phenomena specific for the evolutionary and genetic algorithms as chromosomes crossover, mutation, selection and reproduction, parents and off-springs.