Journal of Engineering and Applied Sciences

Year: 2017
Volume: 12
Issue: 9 SI
Page No. 8531 - 8536

A Conceptual Framework of Bacterial Foraging Optimization Algorithm for Data Classification

Authors : M. Hossin and F. Mohd Suria

References

Aouidate, M.A. and A.A.R. Baba, 2012. A Hybrid KNN-Ant Colony Optimization Algorithm for Prototype Selection. In: Neural Information Processing, Huang, T., Z. Zeng, C. Li and C.S. Leung (Eds.). Springer, Berlin, Germany, pp: 307-314.

Aouidate, M.A. and A.A.R. Baba, 2013. An efficient ant colony instance selection algorithm for KNN classification. Intl. J. Appl. Metah. Comput., 4: 47-64.
CrossRef  |  Direct Link  |  

Bensujin, B., C.K.S. Vijila, J. Hemanth and C. Hubert, 2016. Frequency dependent adaptive chemotaxis in bacterial foraging optimization for ST segment elevation myocardial infarction prediction. Indian J. Sci. Technol., Vol. 9, 10.17485/ijst/2016/v9i1/71685

Cano, J.R., F. Herrera and M. Lozano, 2005. Instance Selection using Evolutionary Algorithms: An Experimental Study. In: Advanced Techniques in Knowledge Discovery and Data Mining, Pal, R.N. and J. Lakhmi (Eds.). Springer, London, Englang, ISBN:978-1-85233-867-1, pp: 127-152.

Chakrabarty, A., O. Choudhury, P. Sarkar, A. Paul and D. Sarkar, 2012. Hyperspectral image classification incorporating bacterial foraging-optimized spectral weighting. Artif. Intell. Res., 1: 63-63.
Direct Link  |  

Chen, C.H., M.T. Su, C.J. Lin and C.T. Lin, 2014. A hybrid of bacterial foraging optimization and particle swarm optimization for evolutionary neural fuzzy classifier. Intl. J. Fuzzy Syst., 16: 422-433.
Direct Link  |  

Das, S., A. Biswas, S. Dasgupta and A. Abraham, 2009. Bacterial Foraging Optimization Algorithm: Theoretical Foundations, Analysis and Applications. In: Foundations of Computational Intelligence, Volume 3: Global Optimization, Abraham, A., A.E. Hassanien, P. Siarry and A. Engelbrecht (Eds.). Springer, Berlin, Germany, ISBN: 9783642010842, pp: 23-55.

Garcia, S., J. Derrac, J. Cano and F. Herrera, 2012. Prototype selection for nearest neighbor classification: Taxonomy and empirical study. IEEE. Trans. Pattern Anal. Mach. Intell., 34: 417-435.
CrossRef  |  Direct Link  |  

Garcia-Pedrajas, N., J.A.R. del Castillo and D. Ortiz-Boyer, 2010. A cooperative coevolutionary algorithm for instance selection for instance-based learning. Mach. Learn., 78: 381-420.
CrossRef  |  

Gil-Pita, R. and X. Yao, 2007. Using a Genetic Algorithm for Editing K-Nearest Neighbor Classifiers. In: Intelligent Data Engineering and Automated Learning, Yin, H., P. Tino, E. Corchado, W. Byrne and X. Yao (Eds.). Springer, Berlin, Germany, pp: 1141-1150.

Hadi, A.I.A.A., S.Z.M. Hashim and S.M.H. Shamsuddin, 2011. Bacterial foraging optimization algorithm for neural network learning enhancement. Proceedings of the 2011 11th International Conference on Hybrid Intelligent Systems (HIS), December 5-8, 2011, IEEE, Johor, Malaysia, ISBN:978-1-4577-2152-6, pp: 200-205.

Hu, W. and Y. Tan, 2016. Prototype generation using multiobjective particle swarm optimization for nearest neighbor classification. IEEE. Trans. Cybern., 46: 2719-2731.
CrossRef  |  Direct Link  |  

Jakhar, R., N. Kaur and R. Singh, 2011. Face recognition using bacteria foraging optimization-based selected features. Intl. J. Adv. Comput. Sci. Appl., 1: 106-111.
Direct Link  |  

Kaur, R. and B. Kaur, 2014. Artificial neural network learning enhancement using bacterial foraging optimization algorithm. Intl. J. Comput. Appl., 102: 27-33.
Direct Link  |  

Kora, P. and S.R. Kalva, 2015. Hybrid bacterial foraging and particle swarm optimization for detecting bundle branch block. Springer Plus, 4: 1-19.
CrossRef  |  PubMed  |  Direct Link  |  

Kuncheva, L.I. and J.C. Bezdek, 1998. Nearst prototype classification: Clustering, genetic algorithms, or random search?. IEEE Trans. Syst., Man, Cyber. Part C, 28: 160-164.
CrossRef  |  Direct Link  |  

Kuncheva, L.I., 1997. Fitness functions in editing K-NN reference set by genetic algorithms. Pattern Recognit., 30: 1041-1049.
Direct Link  |  

Pal, M., S. Bhattacharyya, S. Roy, A. Konar and D.N. Tibarewala et al., 2014. A bacterial foraging optimization and learning automata based feature selection for motor imagery EEG classification. Proceedings of the 2014 International Conference on Signal Processing and Communications (SPCOM), July 22-25, 2014, IEEE, Kolkata, India, ISBN:978-1-4799-4665-5, pp: 1-5.

Passino, K.M., 2002. Biomimicry of bacterial foraging for distributed optimization and control. IEEE Control Syst., 22: 52-67.
CrossRef  |  

Putra, I.K.G.D. and S. Kom, 2014. Optimized back propagation learning in neural networks with bacterial foraging optimization to predict forex gold index (XAUUSD). Appl. Math. Sci., 8: 37-40.
CrossRef  |  Direct Link  |  

Qiang, S. ansd A.W.A.N.G. Min, 2013. A hybrid algorithm based on ls-svm and bacterial foraging approach for Burning-Through-Points (BTP) prediction in sintering process. J. Theor. Appl. Inf. Technol., 49: 231-240.
Direct Link  |  

Rani, B., A.K. Goel and R.A. Kaur, 2016. Modified approach for lung cancer detection using bacterial foraging optimization algorithm. Intl. J. Sci. Res. Eng. Technol., 5: 39-42.

Rani, D. and V. Mangat, 2013. An efficient technique for disease diagnosis using bacterial foraging optimization and artificial neural network. Proceedings of the 2013 International Symposium on Computational and Business Intelligence (ISCBI), August 24-26, 2013, IEEE, Chandigarh, India, ISBN:978-0-7695-5066-4, pp: 100-104.

Sindhu, V., 2016. An efficient technique to cancer classification using fast improved bacterial foraging optimization. Intl. J. Recent Trends Eng. Res., 2: 436-441.

Suguna, N. and K. Thanushkodi, 2010. An improved k-nearest neighbor classification using genetic algorithm. Int. J. Comput. Sci. Issues, 7: 18-21.

Varghese, T., R.S. Kumari, P.S. Mathuranath and N.A. Singh, 2012. Performance Evaluation of Bacterial Foraging Optimization Algorithm for the Early Diagnosis and Tracking of Alzheimer’s Disease. In: Swarm, Evolutionary and Memetic Computing, Panigrahi, B.K., S. Das, P.N. Suganthan and P.K. Nanda (Eds.). Springer, Berlin, Germany, pp: 41-48.

Wan, M., L. Li, J. Xiao, C. Wang and Y. Yang, 2012. Data clustering using bacterial foraging optimization. J. Intell. Inf. Syst., 38: 321-341.
CrossRef  |  Direct Link  |  

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