Abstract
In Data mining, Fuzzy or soft clustering is one of the popular approaches proposed to solve several real-world problems. The Fuzzy C-Means (FCM) algorithm is the famous algorithm in fuzzy clustering because of its straightforwardness and short computational effort. But it has the problem of local optima. To overcome this local optima problem, many optimization algorithms have been developed and try to attain a global optimum solution. In this research work, two kinds of enhancement are proposed to solve clustering problem and overcome the above-mentioned shortcomings. First, Bacterial Colony Optimization (BCO) algorithm is integrated with fuzzy theory called Fuzzy BCO (FBCO). Second, Hybridization of FCM with FBCO is developed to obtaining good optimal clusters are called as Hybridization of Fuzzy Clustering Algorithms (HFCA). The experimental results of proposed algorithms are demonstrated using six machine learning datasets and the results produced by proposed FBCO and HFCA generates higher performance while match up with FCM, FPSO (Fuzzy Particle Swarm Optimization) and FBFO (Fuzzy Bacterial Foraging Optimization) algorithms.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Similar content being viewed by others
References
N.R. Pal, K. Pal, J.M. Keller, J.C. Bezdek, A possibilistic fuzzy c-means clustering algorithm. IEEE Trans. Fuzzy Syst. 13, 517–530 (2005)
J.C. Bezdek, R. Ehrlich, W. Full, FCM: the fuzzy c-means clustering algorithm. Comput. Geosci. 10, 191–203 (1984)
Chuang, K.-S., Tzeng, H.-L., Chen, S., Wu, J., Chen, T.-J., Fuzzy c-means clustering with spatial information for image segmentation. Comput. Med. Imaging Graph. 30, 9–15 (2006)
A. Bose, K. Mali, Fuzzy-based artificial bee colony optimization for gray image segmentation. SIViP 10, 1089–1096 (2016)
S. Alam, G. Dobbie, Y.S. Koh, P. Riddle, S.U. Rehman, Research on particle swarm optimization based clustering: a systematic review of literature and techniques. Swarm Evol. Comput. 17, 1–13 (2014)
T. Cura, A particle swarm optimization approach to clustering. Expert Syst. Appl. 39, 1582–1588 (2012)
T.A. Runkler, C. Katz, Fuzzy clustering by particle swarm optimization. IEEE Int. Conf. Fuzzy Syst. 2006, 601–608 (2006)
C. Li, J. Zhou, P. Kou, J. Xiao, A novel chaotic particle swarm optimization based fuzzy clustering algorithm. Neurocomputing 83, 98–109 (2012)
J. Senthilnath, S. Omkar, V. Mani, Clustering using firefly algorithm: performance study. Swarm Evol Comput 1, 164–171 (2011)
M. Wan, L. Li, J. Xiao, C. Wang, Y. Yang, Data clustering using bacterial foraging optimization. J Intell Inf Syst 38, 321–341 (2012)
K.M. Passino, Biomimicry of bacterial foraging for distributed optimization and control. IEEE Control Syst. Mag. 22, 52–67 (2002)
S.D. Muller, J. Marchetto, S. Airaghi, P. Kournoutsakos, Optimization based on bacterial chemotaxis. IEEE Trans. Evol. Comput. 6, 16–29 (2002)
Niu, B., Wang, H., Bacterial colony optimization. Discrete Dyn. Nat. Soc. (2012)
P. Padmavathi, V. Eswaramurthy, J. Revathi, Fuzzy social spider optimization algorithm for fuzzy clustering analysis. Int. Conf. Current Trends Towards Converg. Technol. (ICCTCT) 2018, 1–6 (2018)
Niu, B., Wang, N., Bacterial colony optimization (2012)
T. Niknam, B. Amiri, An efficient hybrid approach based on PSO, ACO and k-means for cluster analysis. Appl. Soft Comput. 10, 183–197 (2010)
U. Maulik, S. Bandyopadhyay, Genetic algorithm-based clustering technique. Pattern Recogn. 33, 1455–1465 (2000)
Vijayakumari, K., Preetha, M., Velusamy, K., Performance analysis of clustering based on fuzzy system
Baalamurugan, K., Bhanu, S.V., An efficient clustering scheme for cloud computing problems using metaheuristic algorithms. Clust. Comput. 1–11 (2018)
D. Karaboga, C. Ozturk, Fuzzy clustering with artificial bee colony algorithm. Sci. Res. Essays 5, 1899–1902 (2010)
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2021 Springer Nature Singapore Pte Ltd.
About this paper
Cite this paper
Vijayakumari, K., Baby Deepa, V. (2021). Fuzzy C-Means Hybrid with Fuzzy Bacterial Colony Optimization. In: Sengodan, T., Murugappan, M., Misra, S. (eds) Advances in Electrical and Computer Technologies. ICAECT 2020. Lecture Notes in Electrical Engineering, vol 711. Springer, Singapore. https://doi.org/10.1007/978-981-15-9019-1_7
Download citation
DOI: https://doi.org/10.1007/978-981-15-9019-1_7
Published:
Publisher Name: Springer, Singapore
Print ISBN: 978-981-15-9018-4
Online ISBN: 978-981-15-9019-1
eBook Packages: Computer ScienceComputer Science (R0)