Binary Whale Optimization Algorithm and Binary Moth Flame Optimization with Clustering Algorithms for Clinical Breast Cancer Diagnoses

Author:

Sayed Gehad Ismail,Darwish Ashraf,Hassanien Aboul Ella

Publisher

Springer Science and Business Media LLC

Subject

Library and Information Sciences,Statistics, Probability and Uncertainty,Psychology (miscellaneous),Mathematics (miscellaneous)

Reference54 articles.

1. Abdel-Basset, M., Shahat, D., Sangaiah, A. (2017). A modied nature inspired meta-heuristic whale optimization algorithm forsolving 01 knapsack problem. International Journal of Machine Learning and Cyber, 1–20.

2. AbdEl-Fattah, S., Nabil, E., Badr, A. (2016). A binary colnal flower pollination algorithm for feature selection. Pattern Recognition Letters, 77, 21–27.

3. Alba, E., & Dorronsoro, B. (2005). The exploration/exploitation tradeoffin dynamic cellular genetic algorithms. IEEE Transaction on Evolutionary Computation, 9(2), 126–142.

4. Arthur, D., & Vassilvitskii, S. (2007). K-means++: the advantages of careful seeding. In Proceedings of the 18th annual acm-siam symposium on discrete algorithms (p. 10271035). PA, USA.

5. Aziz, M., Ewees, A., Hassanien, A. (2017). Whale optimization algorithm and moth-flame optimization for multilevel thresholding image segmentation. Expert Systems with Applications, 1–33.

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