An enhanced fuzzy min-max neural network with ant colony optimization based-rule-extractor for decision making

This paper proposes an enhanced fuzzy minmax neural (EFMN) network model with ant colony optimization based-rule-extractor for grouping of the data-patterns and decision making by rule-list. There are many methods to extract the rules which are having less accuracy and with less performance. The earlier methods have drawbacks like they have not maintained the rule accuracy in terms of consistency. The proposed method has improved the accuracy, consistency and performance against existing methods. The number of rules obtained from this system is less in count and having higher rank. One of the strength of this method is that the rules obtained from the system are comprehensible, as they are in rule list format. This rule list is useful in decision making problem.

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