Activation and defuzzification methods for fuzzy rule-based systems
In this paper, a Selective Inference Engine (SIE) is first proposed. SIE predicts the rules that will be fired, based on an anticipated location procedure, and then performs the inference calculations only on the latter. This anticipated location is based on the projection of the input data on the conditional space of the fuzzy system and the delimitation of the excited region. Then, the fired rules can be aggregated using the appropriate scheme. In the second part of this work, we propose new defuzzification methods which take into account the consequent membership function shapes.
defuzzification methods inference fuzzy systems rule activation