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Aziz, A. S. A., A. T. Azar, M. A. Salama, A. E. Hassanien, and S. E. - O. Hanafy, "Genetic algorithm with different feature selection techniques for anomaly detectors generation", Computer Science and Information Systems (FedCSIS), 2013 Federated Conference on: IEEE, pp. 769–774, 2013. Abstract
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Al-Qaheri, H., A. E. Hassanien, and A. Abraham, "A Generic Scheme for Generating Prediction Rules Using Rough Sets", Rough Set Theory: A True Landmark in Data Analysis: Springer Berlin Heidelberg, pp. 163–186, 2009. Abstract
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Al-Qaheri, H., A. E. Hassanien, and A. Abraham, "A Generic Scheme for Generating Prediction Rules Using Rough Sets", Rough Set Theory: A True Landmark in Data Analysis: Springer Berlin Heidelberg, pp. 163–186, 2009. Abstract
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Hassanien, A. E., H. Karam, H. Akter, and M. Nakajima:, "Generation of Missing Medical Slices Using Morphing Technology", Proceedings of IAPR Workshop on Machine Vision Applications, MVA 1998,, Chiba, Japan, November 17-19, 1998.
Haque, H., A. - E. Hassanien, and M. Nakajima, "Generation of missing medical slices using morphing technology", IEICE TRANSACTIONS on Information and Systems, vol. 83, no. 7: The Institute of Electronics, Information and Communication Engineers, pp. 1400–1407, 2000. Abstract
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Haque, H., A. - E. Hassanien, and M. Nakajima, "Generation of missing medical slices using morphing technology", IEICE TRANSACTIONS on Information and Systems, vol. 83, no. 7: The Institute of Electronics, Information and Communication Engineers, pp. 1400–1407, 2000. Abstract
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Hasnine, A. E. H. H. K., and A. M. NAKAJIMA, Generation of Missing Mcdical Slices Using Morphing Technology, , 1998. Abstract
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Hassanien, A. E., S. H. Basha, and A. S. Abdalla, "Generalization of Fuzzy C-Means Based on Neutrosophic Logic", Studies in Informatics and Control, vol. 27, issue 1, pp. 43-54, , 2018. Abstract

This article presents a New Neutrosophic C-Means (NNCMs) method for clustering. It uses the neutrosophic logic (NL), to generalize the Fuzzy C-Means (FCM) clustering system. The NNCMs system assigns objects to clusters using three degrees of membership: a degree of truth, a degree of indeterminacy, and a degree of falsity, rather than only the truth degree used in the FCM. The indeterminacy degree, in the NL, helps in categorizing objects laying in the intersection and the boundary areas. Therefore, the NNCMs reaches more accurate results in clustering. These degrees are initialized randomly without any constraints. That is followed by calculating the clusters’ centers. Then, iteratively, the NNCMs updates the membership values of every object, and the clusters’ centers. Finally, it measures the accuracy and tests the objective function. The performance of the proposed system is tested on the six real-world databases: Iris, Wine, Wisconsin Diagnostic Breast Cancer, Seeds, Pima, and Statlog (Heart). The comparison between the two systems shows that the proposed NNCMs is more accurate.

Wahid, R., N. I. Ghali, H. S. Own, T. - H. Kim, and A. E. Hassanien, "A Gaussian mixture models approach to human heart signal verification using different feature extraction algorithms", Computer Applications for Bio-technology, Multimedia, and Ubiquitous City: Springer Berlin Heidelberg, pp. 16–24, 2012. Abstract
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Wahid, R., N. I. Ghali, H. S. Own, T. - H. Kim, and A. E. Hassanien, "A Gaussian mixture models approach to human heart signal verification using different feature extraction algorithms", Computer Applications for Bio-technology, Multimedia, and Ubiquitous City: Springer Berlin Heidelberg, pp. 16–24, 2012. Abstract
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Fattah, M. A., N. Elbendary, H. K. Elminir, M. A. A. El-Soud, and A. E. Hassanien, "Galaxies image classification using empirical mode decomposition and machine learning techniques ", The second International Conference on Engineering and Technology (ICET 2014) , German Uni - Cairo Egypt, 19 Apr - 20 Apr , 2014.
Fattah, M. A., N. Elbendary, H. K. Elminir, M. A. A. El-Soud, and A. E. Hassanien, "Galaxies image classification using empirical mode decomposition and machine learning techniques", Engineering and Technology (ICET), 2014 International Conference on: IEEE, pp. 1–5, 2014. Abstract
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