Applying the Fuzzy Ant-Miner Algorithm to Extract the Success Indicators of Balloon Dilation in PA-IVS
International Journal of Intelligent Information Systems
Volume 5, Issue 3-1, May 2016, Pages: 1-4
Received: Oct. 10, 2015;
Accepted: Oct. 12, 2015;
Published: Jun. 18, 2016
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Mohamed Hamlich, Computer science lab, UH2, FSTM, Mohammedia, Morocco
Mohammed Ramdani, Computer science lab, UH2, FSTM, Mohammedia, Morocco
Several studies have sought to identify the parameters that determine the outcome of balloon dilation in pulmonary atresia with ventricular septum. However, none of these studies was based on the ant colony algorithm. In this paper we focus on the implementation of an algorithm based on ant colonies: Fuzzy Ant-Miner. This method uses the concepts of fuzzy logic to extract rules from the training data. These rules are exploited using a Mamdani fuzzy inference system for classification and prediction. The results obtained by this method in the form of fuzzy rules are easy to interpret, and close to human reasoning.
Applying the Fuzzy Ant-Miner Algorithm to Extract the Success Indicators of Balloon Dilation in PA-IVS, International Journal of Intelligent Information Systems. Special Issue: Smart Applications and Data Analysis for Smart Cities.
Vol. 5, No. 3-1,
2016, pp. 1-4.
Copyright © 2016 Authors retain the copyright of this article.
This article is an open access article distributed under the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/
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