Data Clustering Using Sine Cosine Algorithm: Data Clustering Using SCA

The clustering techniques suffer from cluster centers initialization and local optima problems. In this chapter, the new metaheuristic algorithm, Sine Cosine Algorithm (SCA), is used as a search method to solve these problems. The SCA explores the search space of given dataset to find out the near-optimal cluster centers. The center based encoding scheme is used to evolve the cluster centers. The proposed SCA-based clustering technique is evaluated on four real-life datasets. The performance of SCA-based clustering is compared with recently developed clustering techniques. The experimental results reveal that SCA-based clustering gives better values in terms of cluster quality measures.

[1]  Shokri Z. Selim,et al.  A simulated annealing algorithm for the clustering problem , 1991, Pattern Recognit..

[2]  Václav Snásel,et al.  Biometric cattle identification approach based on Weber's Local Descriptor and AdaBoost classifier , 2016, Comput. Electron. Agric..

[3]  Anil K. Jain,et al.  Data clustering: a review , 1999, CSUR.

[4]  Hichem Frigui,et al.  A Robust Competitive Clustering Algorithm With Applications in Computer Vision , 1999, IEEE Trans. Pattern Anal. Mach. Intell..

[5]  Bo Liu.  Composite Differential Search Algorithm , 2014, J. Appl. Math..

[6]  Xin-She Yang,et al.  A New Metaheuristic Bat-Inspired Algorithm , 2010, NICSO.

[7]  Kamel Nadjet,et al.  A New Algorithm for Data Clustering Based on Cuckoo Search Optimization , 2014, ICGEC 2014.

[8]  Ganapati Panda,et al.  A survey on nature inspired metaheuristic algorithms for partitional clustering , 2014, Swarm Evol. Comput..

[9]  Dantong Ouyang,et al.  An artificial bee colony approach for clustering , 2010, Expert Syst. Appl..

[10]  C. A. Murthy,et al.  In search of optimal clusters using genetic algorithms , 1996, Pattern Recognit. Lett..

[11]  Salwani Abdullah,et al.  Data Clustering Using Big Bang–Big Crunch Algorithm , 2011 .

[12]  Ujjwal Maulik,et al.  Genetic algorithm-based clustering technique , 2000, Pattern Recognit..

[13]  B. Kulkarni,et al.  An ant colony approach for clustering , 2004 .

[14]  Anil K. Jain.  Data clustering: 50 years beyond K-means , 2010, Pattern Recognit. Lett..

[15]  Mohammad Reza Meybodi,et al.  A new hybrid approach for data clustering using firefly algorithm and K-means , 2012, The 16th CSI International Symposium on Artificial Intelligence and Signal Processing (AISP 2012).

[16]  Dinesh Kumar,et al.  Parameter adaptive harmony search algorithm for unimodal and multimodal optimization problems , 2014, J. Comput. Sci..

[17]  Dinesh Kumar,et al.  VARIANCE-BASED HARMONY SEARCH ALGORITHM FOR UNIMODAL AND MULTIMODAL OPTIMIZATION PROBLEMS WITH APPLICATION TO CLUSTERING , 2014, Cybern. Syst..

[18]  Erwie Zahara,et al.  A hybridized approach to data clustering , 2008, Expert Syst. Appl..

[19]  Andries Petrus Engelbrecht,et al.  Dynamic clustering using particle swarm optimization with application in image segmentation , 2006, Pattern Analysis and Applications.

[20]  Ali Maroosi,et al.  Application of honey-bee mating optimization algorithm on clustering , 2007, Appl. Math. Comput..

[21]  Ji Wang,et al.  Counterexample-Preserving Reduction for Symbolic Model Checking , 2013, ICTAC.

[22]  D. Karaboga,et al.  On the performance of artificial bee colony (ABC) algorithm , 2008, Appl. Soft Comput..

[23]  Ajith Abraham,et al.  Swarm Intelligence Algorithms for Data Clustering , 2008, Soft Computing for Knowledge Discovery and Data Mining.

[24]  Seyedali Mirjalili,et al.  SCA: A Sine Cosine Algorithm for solving optimization problems , 2016, Knowl. Based Syst..

[25]  Yee Leung,et al.  Clustering by Scale-Space Filtering , 2000, IEEE Trans. Pattern Anal. Mach. Intell..

[26]  Salwani Abdullah,et al.  Application of Gravitational Search Algorithm on Data Clustering , 2011, RSKT.

[27]  Aboul Ella Hassanien,et al.  A New Multi-layer Perceptrons Trainer Based on Ant Lion Optimization Algorithm , 2015, 2015 Fourth International Conference on Information Science and Industrial Applications (ISI).

[28]  M. Narasimha Murty,et al.  Genetic K-means algorithm , 1999, IEEE Trans. Syst. Man Cybern. Part B.

[29]  Abdolreza Hatamlou,et al.  Black hole: A new heuristic optimization approach for data clustering , 2013, Inf. Sci..

[30]  Xin-She Yang,et al.  Flower Pollination Algorithm for Global Optimization , 2012, UCNC.

[31]  Chang Sup Sung,et al.  A tabu-search-based heuristic for clustering , 2000, Pattern Recognit..

[32]  Dinesh Kumar,et al.  Automatic MRI Brain Image Segmentation Using Gravitational Search-Based Clustering Technique , 2017 .

[33]  Abdolreza Hatamlou,et al.  Hybridization of the Gravitational Search Algorithm and Big Bang-Big Crunch Algorithm for Data Clustering , 2013, Fundam. Informaticae.

[34]  Ujjwal Maulik,et al.  An evolutionary technique based on K-Means algorithm for optimal clustering in RN , 2002, Inf. Sci..

[35]  Anima Naik,et al.  Data Clustering Based on Teaching-Learning-Based Optimization , 2011, SEMCCO.

[36]  Aboul Ella Hassanien,et al.  Moth-flame optimization for training Multi-Layer Perceptrons , 2015, 2015 11th International Computer Engineering Conference (ICENCO).