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.
| Published in |
International Journal of Intelligent Information Systems (Volume 5, Issue 3-1)
This article belongs to the Special Issue Smart Applications and Data Analysis for Smart Cities |
| DOI | 10.11648/j.ijiis.s.2016050301.11 |
| Page(s) | 1-4 |
| Creative Commons |
This is an Open Access article, distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution and reproduction in any medium or format, provided the original work is properly cited. |
| Copyright |
Copyright © The Author(s), 2016. Published by Science Publishing Group |
Atresia with Intact Ventricular Septum, Balloon Dilation, Fuzzy Ant-Miner, Fuzzy Partitions, Fuzzy Rules
| [1] | A. Drighil, M. Aljufan, A. Slimi, S. Yamani, J. Mathewson, F. AlFadly”, Echocardiographic determinants of successful balloon dilation in pulmonary atresia with intact ventricular septum”, European Journal of Echocardiography (2010) 11, 172–175 doi:10.1093/ejechocard/jep193 |
| [2] | Parpinelli, R., Lopes, H., Freitas, A. (2002). “Data mining with an ant colony optimization algorithm,” IEEE. Transactions on Evolutionary Computation, vol. 6, no. 4, pp. 321–332. |
| [3] | M. Hamlich and M. Ramdani, “Data classification by Fuzzy Ant-Miner”, IJCSI International Journal of Computer Sciences issues, Vol 9, Issue 2, N° 3, Marsh 2012, ISSN (Online) 1694-08 14.. |
| [4] | M. Hamlich and, M. Ramdani, “Scout Ants for Clustering”, Journal of Theoretical and Applied Information Technology (JATIT), September 2013 -- Vol. 55. No. 1 -- 2013. |
| [5] | M. Hamlich and, M. Ramdani, ”Ant Colony algorithms for data learning”, International Journal of Applied Evolutionary Computation (IJAEC), Volume 4, Issue 3, pp 1-10. July-September 2013. |
| [6] | M. Hamlich and M. Ramdani, «Improved ant colony algorithms for data classification», ISBN: 978-1-4673-4764-8, IEEE Xplore. |
| [7] | M. Hamlich and, M. Ramdani, “Fuzzy classification by ant colonies”, Seventh Iinternational Conference on Intelligent Systems: Theories and Applications (SITA'12) 16-17 MAY 2012, Mohammedia, Morocco. |
| [8] | M. Hamlich and, M. Ramdani, “Fuzzy Ant-Miner”, IADIS European Conference Data Mining 2012, Lisboa Portugal, ISBN 978-972-8939-69-4. |
| [9] | Otero, F. Freitas, A, and C. G. Johnson (2008), “cAnt-Miner: an ant colony classification algorithm to cope with continuous attributes,” in Ant Colony Optimization and Swarm Intelligence, LNCS 5217. Springer, pp. 48–59. |
| [10] | M. Hamlich and M. Ramdani, «Improved ant colony algorithms for data classification », International Conference on Complex Systems (ICCS), Agadir, Morocco, ISBN: 978-1-4673-4764-8, November 05-06, 2012. |
APA Style
Mohamed Hamlich, Mohammed Ramdani. (2016). Applying the Fuzzy Ant-Miner Algorithm to Extract the Success Indicators of Balloon Dilation in PA-IVS. International Journal of Intelligent Information Systems, 5(3-1), 1-4. https://doi.org/10.11648/j.ijiis.s.2016050301.11
ACS Style
Mohamed Hamlich; Mohammed Ramdani. Applying the Fuzzy Ant-Miner Algorithm to Extract the Success Indicators of Balloon Dilation in PA-IVS. Int. J. Intell. Inf. Syst. 2016, 5(3-1), 1-4. doi: 10.11648/j.ijiis.s.2016050301.11
AMA Style
Mohamed Hamlich, Mohammed Ramdani. Applying the Fuzzy Ant-Miner Algorithm to Extract the Success Indicators of Balloon Dilation in PA-IVS. Int J Intell Inf Syst. 2016;5(3-1):1-4. doi: 10.11648/j.ijiis.s.2016050301.11
Share This Article
Twitter
Linked In
Facebook
Copy
Download@article{10.11648/j.ijiis.s.2016050301.11,
author = {Mohamed Hamlich and Mohammed Ramdani},
title = {Applying the Fuzzy Ant-Miner Algorithm to Extract the Success Indicators of Balloon Dilation in PA-IVS},
journal = {International Journal of Intelligent Information Systems},
volume = {5},
number = {3-1},
pages = {1-4},
doi = {10.11648/j.ijiis.s.2016050301.11},
url = {https://doi.org/10.11648/j.ijiis.s.2016050301.11},
eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.ijiis.s.2016050301.11},
abstract = {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.},
year = {2016}
}
TY - JOUR T1 - Applying the Fuzzy Ant-Miner Algorithm to Extract the Success Indicators of Balloon Dilation in PA-IVS AU - Mohamed Hamlich AU - Mohammed Ramdani Y1 - 2016/06/18 PY - 2016 N1 - https://doi.org/10.11648/j.ijiis.s.2016050301.11 DO - 10.11648/j.ijiis.s.2016050301.11 T2 - International Journal of Intelligent Information Systems JF - International Journal of Intelligent Information Systems JO - International Journal of Intelligent Information Systems SP - 1 EP - 4 PB - Science Publishing Group SN - 2328-7683 UR - https://doi.org/10.11648/j.ijiis.s.2016050301.11 AB - 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. VL - 5 IS - 3-1 ER -
Email: