International Journal of Approximate Reasoning
Knowledge-based Intelligent Diagnosis of Ground Robot Collision with Non Detectable Obstacles
Journal of Intelligent and Robotic Systems
Optimization of fuzzy partitions for inductive reasoning using genetic algorithms
International Journal of Systems Science
Commutativity as prior knowledge in fuzzy modeling
Fuzzy Sets and Systems
Recent Literature Collected by Didier DUBOIS, Henri PRADE and Salvatore SESSA
Fuzzy Sets and Systems
Commutativity as prior knowledge in fuzzy modeling
IFSA'03 Proceedings of the 10th international fuzzy systems association World Congress conference on Fuzzy sets and systems
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With identification methods that learn fuzzy rules directly from certainty degrees, we refer to methods that select the most promising rules from the training examples in only one pass. In order to do that, these methods employ a certainty measure to assess the goodness of each rule. This paper aims to analyze in depth the behaviors and features of two different strategies for identifying fuzzy models from certainty degrees, each of both combined with one of two well-known alternatives for measuring the certainty degrees of the rules. With this aim, the advantages and drawbacks of each method are analyzed experimentally by considering the model error when applied to several systems. Besides, the robustness of the results is investigated by applying the methods to noisy data. As a conclusion, a new method combining the best components of the previously considered methods is proposed and its results are analyzed. The achieved performance in accuracy and computational cost shows the benefit of this new method.