{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2024,9,12]],"date-time":"2024-09-12T05:09:31Z","timestamp":1726117771250},"reference-count":101,"publisher":"Springer Science and Business Media LLC","issue":"12","license":[{"start":{"date-parts":[[2015,6,5]],"date-time":"2015-06-05T00:00:00Z","timestamp":1433462400000},"content-version":"tdm","delay-in-days":0,"URL":"http:\/\/www.springer.com\/tdm"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["Soft Comput"],"published-print":{"date-parts":[[2015,12]]},"DOI":"10.1007\/s00500-015-1719-0","type":"journal-article","created":{"date-parts":[[2015,6,4]],"date-time":"2015-06-04T17:45:38Z","timestamp":1433439938000},"page":"3621-3645","update-policy":"http:\/\/dx.doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":26,"title":["Hybridization of magnetic charge system search and particle swarm optimization for efficient data clustering using neighborhood search strategy"],"prefix":"10.1007","volume":"19","author":[{"given":"Y.","family":"Kumar","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"G.","family":"Sahoo","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2015,6,5]]},"reference":[{"key":"1719_CR1","unstructured":"Abraham A, Das S, Roy S (2007) Swarm intelligence algorithms for data clustering. In: Soft computing for knowledge discovery and data mining, part IV. Springer, Berlin, pp 79\u2013313"},{"key":"1719_CR2","unstructured":"Alpaydin E (2004) Introduction to machine learning. MIT Press, Cambridge"},{"key":"1719_CR3","volume-title":"Cluster analysis for application","author":"MR Anderberg","year":"1973","unstructured":"Anderberg MR (1973) Cluster analysis for application. Academic Press, New York"},{"key":"1719_CR4","doi-asserted-by":"crossref","unstructured":"Ankerst M, Breunig M, Kriegel HP, Sander J (1999) OPTICS: ordering points to identify the clustering structure. In: Proceedings of the 1999 ACM-SIGMOD international conference on management of data, Philadelphia, pp 49\u201360","DOI":"10.1145\/304182.304187"},{"issue":"21","key":"1719_CR5","doi-asserted-by":"crossref","first-page":"2952","DOI":"10.1093\/bioinformatics\/btm410","volume":"23","author":"J Archer","year":"2007","unstructured":"Archer J, Robertson DL (2007) CTree: comparison of clusters between phylogenetic trees made easy. Bioinformatics 23(21):2952\u20132953","journal-title":"Bioinformatics"},{"key":"1719_CR6","doi-asserted-by":"crossref","first-page":"153","DOI":"10.1002\/bs.3830120210","volume":"12","author":"G Ball","year":"1967","unstructured":"Ball G, Hall D (1967) A clustering technique for summarizing multivariate data. Behav Sci 12:153\u2013155","journal-title":"Behav Sci"},{"key":"1719_CR7","unstructured":"Basu S, Davidson I, Wagstaff K (2008) Constrained clustering: advances in algorithms. In: Theory and applications, data mining and knowledge discovery. Chapman and Hall\/CRC, London"},{"key":"1719_CR8","doi-asserted-by":"crossref","DOI":"10.1007\/978-1-4757-0450-1","volume-title":"Pattern recognition with fuzzy objective function algorithms. Advanced applications in pattern recognition","author":"J Bezdek","year":"1981","unstructured":"Bezdek J (1981) Pattern recognition with fuzzy objective function algorithms. Advanced applications in pattern recognition. Plenum Press, New York"},{"key":"1719_CR9","doi-asserted-by":"crossref","unstructured":"Bezdek JC, Boggavarapu S, Hall LO, Bensaid A (1994) Genetic algorithm guided clustering. In: IEEE World Congress on computational intelligence and evolutionary computation, pp 34\u201339","DOI":"10.1109\/ICEC.1994.350046"},{"issue":"6","key":"1719_CR10","doi-asserted-by":"crossref","first-page":"888","DOI":"10.1162\/neco.1992.4.6.888","volume":"4","author":"L Bottou","year":"1992","unstructured":"Bottou L, Vapnik V (1992) Local learning algorithms. Neural Comput 4(6):888\u2013900","journal-title":"Neural Comput"},{"issue":"2","key":"1719_CR11","first-page":"123","volume":"24","author":"L Breiman","year":"1996","unstructured":"Breiman L (1996) Bagging predictors. Mach Learn 24(2):123\u2013140","journal-title":"Mach Learn"},{"key":"1719_CR12","doi-asserted-by":"crossref","first-page":"54","DOI":"10.1016\/S0734-189X(87)80014-2","volume":"37","author":"GA Carpenter","year":"1987","unstructured":"Carpenter GA, Grossberg S (1987) A massively parallel architecture for a self-organizing neural pattern recognition machine. Comput Vis Graph Image Process 37:54\u2013115","journal-title":"Comput Vis Graph Image Process"},{"issue":"5","key":"1719_CR13","doi-asserted-by":"crossref","first-page":"781","DOI":"10.1016\/0031-3203(94)00125-6","volume":"28","author":"G Celeux","year":"1995","unstructured":"Celeux G, Govaert G (1995) Gaussian parsimonious clustering models. Pattern Recog 28(5):781\u2013793","journal-title":"Pattern Recog"},{"key":"1719_CR14","volume-title":"Advances in knowledge discovery and data mining","author":"P Cheeseman","year":"1996","unstructured":"Cheeseman P, Stutz J (1996) Bayesian classification (AutoClass): theory and results. In: Fayyard UM, Piatetsky-Shapiro G, Smyth P, Uthurusamy R (eds) Advances in knowledge discovery and data mining. AAAI\/MIT Press, Cambridge"},{"key":"1719_CR15","first-page":"165","volume":"6","author":"G Chechik","year":"2005","unstructured":"Chechik G, Globerson A, Tishby N, Weiss Y (2005) Information bottleneck for Gaussian variables. J Mach Learn Res 6:165\u2013188","journal-title":"J Mach Learn Res"},{"issue":"2","key":"1719_CR16","doi-asserted-by":"crossref","first-page":"117","DOI":"10.1049\/el:19950085","volume":"31","author":"S Chen","year":"1995","unstructured":"Chen S (1995) Nonlinear time series modelling and prediction using Gaussian RBF networks with enhanced clustering and RLS learning. Electron Lett 31(2):117\u2013118","journal-title":"Electron Lett"},{"key":"1719_CR17","doi-asserted-by":"crossref","unstructured":"Chi SC, Yang CC (2006) Integration of ant colony SOM and k-means for clustering analysis. In: Knowledge-based intelligent information and engineering systems. Springer, Berlin, pp 1\u20138","DOI":"10.1007\/11892960_1"},{"key":"1719_CR18","unstructured":"Chen CY, Ye F (2004) Particle swarm optimization algorithm and its application to clustering analysis. In: IEEE international conference on networking, sensing and control, vol 2, pp 789\u2013794"},{"key":"1719_CR19","doi-asserted-by":"crossref","unstructured":"Dalli A (2003) Adaptation of the F-measure to cluster based lexicon quality evaluation. In: Proceedings of the EACL, pp 51\u201360","DOI":"10.3115\/1641396.1641404"},{"key":"1719_CR20","unstructured":"Das S, Abraham A, Konar A (2009) Meta-heuristic clustering. Springer, Berlin"},{"issue":"3","key":"1719_CR21","doi-asserted-by":"crossref","first-page":"174","DOI":"10.1016\/j.ijar.2005.11.001","volume":"42","author":"P Dawyndt","year":"2006","unstructured":"Dawyndt P, De Meyer H, De Baets B (2006) UPGMA clustering revisited: a weight-driven approach to transitive approximation. Int J Approx Reason 42(3):174\u2013191","journal-title":"Int J Approx Reason"},{"issue":"1","key":"1719_CR22","doi-asserted-by":"crossref","first-page":"7","DOI":"10.1007\/BF01890115","volume":"1","author":"WH Day","year":"1984","unstructured":"Day WH, Edelsbrunner H (1984) Efficient algorithms for agglomerative hierarchical clustering methods. J Classif 1(1):7\u201324","journal-title":"J Classif"},{"key":"1719_CR23","doi-asserted-by":"crossref","unstructured":"Demiroz G, Guvenir A (1997) Classification by voting feature intervals. In: Proceedings of the seventh european conference on machine learning, pp 85\u201392","DOI":"10.1007\/3-540-62858-4_74"},{"key":"1719_CR24","first-page":"1","volume":"7","author":"J Demsar","year":"2006","unstructured":"Demsar J (2006) Statistical comparisons of classifiers over multiple data sets. J Mach Learn Res 7:1\u201330","journal-title":"J Mach Learn Res"},{"issue":"1","key":"1719_CR25","doi-asserted-by":"crossref","first-page":"3","DOI":"10.1016\/j.swevo.2011.02.002","volume":"1","author":"J Derrac","year":"2011","unstructured":"Derrac J, Garc\u00eda S, Molina D, Herrera F (2011) A practical tutorial on the use of nonparametric statistical tests as a methodology for comparing evolutionary and swarm intelligence algorithms. Swarm Evol Comput 1(1):3\u201318","journal-title":"Swarm Evol Comput"},{"key":"1719_CR26","doi-asserted-by":"crossref","unstructured":"Dorigo M, Maniezzo V, Colorni A (1996) Ant system: optimization by a colony of cooperating agents. IEEE Trans Syst Man Cybern Part B: Cybern 26(1):29\u201341","DOI":"10.1109\/3477.484436"},{"issue":"11","key":"1719_CR27","doi-asserted-by":"crossref","first-page":"1299","DOI":"10.1021\/jm00233a009","volume":"19","author":"WJ Dunn III","year":"1976","unstructured":"Dunn WJ III, Greenberg MJ, Soledad SC (1976) Use of cluster analysis in the development of structure\u2013activity relations for antitumor triazenes. J Med Chem 19(11):1299\u20131301","journal-title":"J Med Chem"},{"issue":"2","key":"1719_CR28","doi-asserted-by":"crossref","first-page":"106","DOI":"10.1016\/j.advengsoft.2005.04.005","volume":"37","author":"OK Erol","year":"2006","unstructured":"Erol OK, Eksin I (2006) A new optimization method: big bang-big crunch. Adv Eng Softw 37(2):106\u2013111","journal-title":"Adv Eng Softw"},{"key":"1719_CR29","doi-asserted-by":"crossref","unstructured":"Esmin AAA, Matwin S (2012) Data clustering using hybrid particle swarm optimization. In: Lecture notes in computer science, pp 159\u2013166","DOI":"10.1007\/978-3-642-32639-4_20"},{"key":"1719_CR30","unstructured":"Ester M, Kriegel HP, Sander J, Xu X (1996) A density based algorithm for discovering clusters in large spatial databases. In: Proceedings of the 1996 international conference on knowledge discovery and data mining (KDD\u201996), Portland, pp 226\u2013231"},{"issue":"2","key":"1719_CR31","doi-asserted-by":"crossref","first-page":"297","DOI":"10.1007\/s003579900058","volume":"16","author":"C Fraley","year":"1999","unstructured":"Fraley C, Raftery AE (1999) MCLUST: software for model-based cluster analysis. J Classif 16(2):297\u2013306","journal-title":"J Classif"},{"key":"1719_CR32","doi-asserted-by":"crossref","unstructured":"Guha S, Rastogi R, Shim K (1998) CURE: an efficient clustering algorithm for large databases. In: Proceedings of the ACM SIGMOD int. conf. management of data, pp 73\u201384","DOI":"10.1145\/276304.276312"},{"issue":"5","key":"1719_CR33","doi-asserted-by":"crossref","first-page":"345","DOI":"10.1016\/S0306-4379(00)00022-3","volume":"25","author":"S Guha","year":"2000","unstructured":"Guha S, Rastogi R, Shim K (2000) ROCK: a robust clustering algorithm for categorical attributes. Inf Syst 25(5):345\u2013366","journal-title":"Inf Syst"},{"issue":"10","key":"1719_CR34","doi-asserted-by":"crossref","first-page":"2044","DOI":"10.1016\/j.ins.2009.12.010","volume":"180","author":"S Garc\u00eda","year":"2010","unstructured":"Garc\u00eda S, Fern\u00e1ndez A, Luengo J, Herrera F (2010) Advanced nonparametric tests for multiple comparisons in the design of experiments in computational intelligence and data mining: Experimental analysis of power. Inf Sci 180(10):2044\u20132064","journal-title":"Inf Sci"},{"issue":"9","key":"1719_CR35","doi-asserted-by":"crossref","first-page":"3763","DOI":"10.1016\/j.asoc.2013.05.012","volume":"13","author":"W Gao","year":"2013","unstructured":"Gao W, Liu SY, Huang LL (2013) A novel artificial bee colony algorithm with Powell\u2019s method. Appl Soft Comput 13(9):3763\u20133775","journal-title":"Appl Soft Comput"},{"key":"1719_CR36","volume-title":"Clustering algorithms","author":"JA Hartigan","year":"1975","unstructured":"Hartigan JA (1975) Clustering algorithms. Wiley, New York"},{"key":"1719_CR37","unstructured":"Handl J, Knowles J, Dorigo M (2003) On the performance of ant-based clustering. In: Design and application of hybrid intelligent system. Frontiers in artificial intelligence and applications, vol 104, pp 204\u2013213"},{"key":"1719_CR38","unstructured":"Hassoun MH (1995) Fundamentals of artificial neural networks. The MIT Press, Cambridge"},{"key":"1719_CR39","doi-asserted-by":"crossref","first-page":"175","DOI":"10.1016\/j.ins.2012.08.023","volume":"222","author":"A Hatamlou","year":"2013","unstructured":"Hatamlou A (2013) Black hole: a new heuristic optimization approach for data clustering. Inf Sci 222:175\u2013184","journal-title":"Inf Sci"},{"issue":"2","key":"1719_CR40","doi-asserted-by":"crossref","first-page":"641","DOI":"10.1016\/j.csda.2006.02.012","volume":"51","author":"Y He","year":"2006","unstructured":"He Y, Pan W, Jizhen L (2006) Cluster analysis using multivariate normal mixture models to detect differential gene expression with microarray data. Comput Stat Data Anal 51(2):641\u2013658","journal-title":"Comput Stat Data Anal"},{"key":"1719_CR41","doi-asserted-by":"crossref","unstructured":"Hruschka ER, Campello RJGB, Freitas AA, De Carvalho ACPLF (2009) A survey of evolutionary algorithms for clustering. IEEE Trans Syst Man Cybern Part C Appl Rev 39(2):133\u2013155","DOI":"10.1109\/TSMCC.2008.2007252"},{"key":"1719_CR42","doi-asserted-by":"crossref","first-page":"420","DOI":"10.1016\/j.knosys.2010.12.003","volume":"24","author":"KY Huang","year":"2011","unstructured":"Huang KY (2011) A hybrid particle swarm optimization approach for clustering and classification of datasets. Knowl Based Syst 24:420\u2013426","journal-title":"Knowl Based Syst"},{"key":"1719_CR43","doi-asserted-by":"crossref","first-page":"651","DOI":"10.1016\/j.patrec.2009.09.011","volume":"31","author":"AK Jain","year":"2010","unstructured":"Jain AK (2010) Data clustering: 50 years beyond K-means. Pattern Recogn Lett 31:651\u2013666","journal-title":"Pattern Recogn Lett"},{"key":"1719_CR44","volume-title":"Algorithms clustering data","author":"AK Jain","year":"1988","unstructured":"Jain AK, Dubes RC (1988) Algorithms clustering data. Prentice-Hall, Englewood cliffs"},{"key":"1719_CR45","unstructured":"Jensen F (1996) An introduction to bayesian networks. UCL Press\/Springer, Berlin"},{"issue":"12","key":"1719_CR46","doi-asserted-by":"crossref","first-page":"8679","DOI":"10.1016\/j.eswa.2010.06.061","volume":"37","author":"H Jiang","year":"2010","unstructured":"Jiang H, Yi S, Li J, Yang F, Hu X (2010) Ant clustering algorithm with K-harmonic means clustering. Expert Syst Appl 37(12):8679\u20138684","journal-title":"Expert Syst Appl"},{"issue":"8","key":"1719_CR47","doi-asserted-by":"crossref","first-page":"9373","DOI":"10.1016\/j.eswa.2011.01.135","volume":"38","author":"H Jiang","year":"2011","unstructured":"Jiang H, Li J, Yi S, Wang X, Hu X (2011) A new hybrid method based on partitioning-based DBSCAN and ant clustering. Expert Syst Appl 38(8):9373\u20139381","journal-title":"Expert Syst Appl"},{"key":"1719_CR48","doi-asserted-by":"crossref","unstructured":"Kao Y, Cheng K (2006) Ant colony optimization and swarm intelligence., An ACO-based clustering algorithm Springer, Berlin","DOI":"10.1007\/11839088_31"},{"issue":"3","key":"1719_CR49","doi-asserted-by":"crossref","first-page":"1754","DOI":"10.1016\/j.eswa.2007.01.028","volume":"34","author":"YT Kao","year":"2008","unstructured":"Kao YT, Zahara E, Kao IW (2008) A hybridized approach to data clustering. Exp Syst Appl 34(3):1754\u20131762","journal-title":"Exp Syst Appl"},{"issue":"3","key":"1719_CR50","doi-asserted-by":"crossref","first-page":"459","DOI":"10.1007\/s10898-007-9149-x","volume":"39","author":"D Karaboga","year":"2007","unstructured":"Karaboga D, Basturk B (2007) A powerful and efficient algorithm for numerical function optimization: artificial bee colony (abc) algorithm. J Global Optim 39(3):459\u2013471","journal-title":"J Global Optim"},{"key":"1719_CR51","doi-asserted-by":"crossref","first-page":"652","DOI":"10.1016\/j.asoc.2009.12.025","volume":"11","author":"D Karaboga","year":"2011","unstructured":"Karaboga D, Ozturk C (2011) A novel clustering approach: artificial bee colony (ABC) algorithm. Appl Soft Comput 11:652\u2013657","journal-title":"Appl Soft Comput"},{"key":"1719_CR52","doi-asserted-by":"crossref","unstructured":"Kaufman L, Rousseeuw P (1990) Finding groups in data: an introduction to cluster analysis. Wiley, New York","DOI":"10.1002\/9780470316801"},{"issue":"3\u20134","key":"1719_CR53","doi-asserted-by":"crossref","first-page":"267","DOI":"10.1007\/s00707-009-0270-4","volume":"213","author":"A Kaveh","year":"2010","unstructured":"Kaveh A, Talatahari S (2010) A novel heuristic optimization method: charged system search. Acta Mechanica 213(3\u20134):267\u2013289","journal-title":"Acta Mechanica"},{"key":"1719_CR54","doi-asserted-by":"crossref","first-page":"15475","DOI":"10.1016\/j.eswa.2011.06.012","volume":"38","author":"A Kaveh","year":"2011","unstructured":"Kaveh A, Laknejadi A (2011) A novel hybrid charge system search and particle swarm optimization method for multi-objective optimization. Exp Syst Appl 38:15475\u201315488","journal-title":"Exp Syst Appl"},{"issue":"1","key":"1719_CR55","doi-asserted-by":"crossref","first-page":"85","DOI":"10.1007\/s00707-012-0745-6","volume":"224","author":"A Kaveh","year":"2013","unstructured":"Kaveh A, Share AMAM, Moslehi M (2013) Magnetic charged system search: a new meta-heuristic algorithm for optimization. Acta Mechanica 224(1):85\u2013107","journal-title":"Acta Mechanica"},{"key":"1719_CR56","doi-asserted-by":"crossref","first-page":"400","DOI":"10.1016\/j.asoc.2014.11.056","volume":"28","author":"A Kaveh","year":"2015","unstructured":"Kaveh A, Mirzaeib B, Jafarvand A (2015) An improved magnetic charged system search for optimization of truss structures with continuous and discrete variables. Appl Soft Comput 28:400\u2013410","journal-title":"Appl Soft Comput"},{"key":"1719_CR57","doi-asserted-by":"crossref","unstructured":"Kennedy J, Eberhart R (1995) Particle swarm optimization. In: Proceeding of IEEE international conference on neural networks (ICW), IV, pp 1942\u20131948","DOI":"10.1109\/ICNN.1995.488968"},{"issue":"9","key":"1719_CR58","doi-asserted-by":"crossref","first-page":"1464","DOI":"10.1109\/5.58325","volume":"78","author":"T Kohonen","year":"1990","unstructured":"Kohonen T (1990) The self-organizing maps. Proc IEEE 78(9):1464\u20131480","journal-title":"Proc IEEE"},{"issue":"3","key":"1719_CR59","doi-asserted-by":"crossref","first-page":"433","DOI":"10.1109\/3477.764879","volume":"29","author":"K Krishna","year":"1999","unstructured":"Krishna K, Murty MN (1999) Genetic k-means algorithm. IEEE Trans Syst Man Cybern Part B Cybern 29(3):433\u2013439","journal-title":"IEEE Trans Syst Man Cybern Part B Cybern"},{"key":"1719_CR60","doi-asserted-by":"crossref","unstructured":"Kumar Y, Sahoo G (2014a) A charged system search approach for data clustering. Progress Artif Intell 2(2\u20133):53\u2013166","DOI":"10.1007\/s13748-014-0049-2"},{"key":"1719_CR61","unstructured":"Kumar Y, Sahoo G (2014b) A chaotic charged system search approach for data clustering. Informatica 38(3):149\u201361"},{"key":"1719_CR62","unstructured":"Kumar Y, Sahoo G (2014c) A hybridize approach for data clustering based on cat swarm optimization. Int J Inf Commun Technol (in Press)"},{"key":"1719_CR63","first-page":"187","volume":"1","author":"Y Kumar","year":"2015","unstructured":"Kumar Y, Sahoo G (2015) An improved cat swarm optimization algorithm for clustering. Comput Intell Data Min 1:187\u2013197","journal-title":"Comput Intell Data Min"},{"key":"1719_CR64","doi-asserted-by":"crossref","unstructured":"Kuo RJ, Lin LM (2010) Application of a hybrid of genetic algorithm and particle swarm optimization algorithm for order clustering. Dec Support Syst 49:451\u2013462","DOI":"10.1016\/j.dss.2010.05.006"},{"issue":"10","key":"1719_CR65","first-page":"1709","volume":"50","author":"RJ Kuo","year":"2005","unstructured":"Kuo RJ, Wang HS, Hu TL, Chou SH (2005) Application of ant K-means on clustering analysis. Comput Math Appl 50(10):1709\u20131724","journal-title":"Comput Math Appl"},{"key":"1719_CR66","doi-asserted-by":"crossref","unstructured":"Lu Y, Lu S, Fotouhi F, Deng Y, Brown SJ (2004) FGKA: a fast genetic k-means clustering algorithm. In: Proceedings of the ACM symposium on applied computing, pp 622\u2013623","DOI":"10.1145\/967900.968029"},{"key":"1719_CR67","unstructured":"MacQueen J (1967) Some methods for classification and analysis of multivariate observations. In: Proceedings of the fifth Berkeley symposium on mathematical statistics and probability, vol 1, pp 281\u2013297"},{"issue":"9","key":"1719_CR68","doi-asserted-by":"crossref","first-page":"1455","DOI":"10.1016\/S0031-3203(99)00137-5","volume":"33","author":"U Maulik","year":"2000","unstructured":"Maulik U, Bandyopadhyay S (2000) Genetic algorithm-based clustering technique. Pattern Recognit 33(9):1455\u20131465","journal-title":"Pattern Recognit"},{"issue":"8","key":"1719_CR69","doi-asserted-by":"crossref","first-page":"1369","DOI":"10.1016\/j.cor.2009.02.025","volume":"37","author":"U Maulik","year":"2010","unstructured":"Maulik U, Mukhopadhyay A (2010) Simulated annealing based automatic fuzzy clustering combined with ANN classification for analyzing microarray data. Comput Oper Res 37(8):1369\u20131380","journal-title":"Comput Oper Res"},{"key":"1719_CR70","volume-title":"The EM algorithm and extensions","author":"G McLachlan","year":"1997","unstructured":"McLachlan G, Krishnan T (1997) The EM algorithm and extensions. Wiley, New York"},{"key":"1719_CR71","unstructured":"Milan S, Hlavac V, Boyle R (1998) Image processing, analysis, and machine vision, 4th edn. Chapman and Hall, London"},{"issue":"6","key":"1719_CR72","doi-asserted-by":"crossref","first-page":"9608","DOI":"10.1016\/j.eswa.2009.01.020","volume":"36","author":"Robert J Mullen","year":"2009","unstructured":"Mullen Robert J, Monekosso Dorothy, Barman Sarah, Remagnino Paolo (2009) A review of ant algorithms. Exp Syst Appl 36(6):9608\u20139617","journal-title":"Exp Syst Appl"},{"key":"1719_CR73","doi-asserted-by":"crossref","unstructured":"Murthy CA, Chowdhury N (1996) In search of optimal clusters using genetic algorithms. Pattern Recognit Lett 17(8):825\u2013832","DOI":"10.1016\/0167-8655(96)00043-8"},{"key":"1719_CR74","doi-asserted-by":"crossref","first-page":"183","DOI":"10.1016\/j.asoc.2009.07.001","volume":"10","author":"T Niknam","year":"2010","unstructured":"Niknam T, Amiri B (2010) An efficient hybrid approach based on PSO, ACO and k-means for cluster analysis. Appl Soft Comput 10:183\u2013197","journal-title":"Appl Soft Comput"},{"key":"1719_CR75","doi-asserted-by":"crossref","unstructured":"Price MN, Dehal PS, Arkin AP (2009) FastTree: computing large minimum evolution trees with profiles instead of a distance matrix. Mol Biol Evol 26(7):1641\u20131650","DOI":"10.1093\/molbev\/msp077"},{"issue":"3","key":"1719_CR76","doi-asserted-by":"crossref","first-page":"303","DOI":"10.1016\/j.cad.2010.12.015","volume":"43","author":"RV Rao","year":"2011","unstructured":"Rao RV, Savsani VJ, Vakharia DP (2011) Teaching-learning-based optimization: a novel method for constrained mechanical design optimization problems. Comput-Aided Des 43(3):303\u2013315","journal-title":"Comput-Aided Des"},{"key":"1719_CR77","series-title":"Modified teacher learning based optimization method for data clustering","volume-title":"Advances in signal processing and intelligent recognition systems","author":"AJ Sahoo","year":"2014","unstructured":"Sahoo AJ, Kumar Y (2014) Advances in signal processing and intelligent recognition systems., Modified teacher learning based optimization method for data clusteringSpringer, Berlin"},{"key":"1719_CR78","doi-asserted-by":"crossref","unstructured":"Santosa B, Ningrum MK (2009) Cat swarm optimization for clustering. In: International conference on soft computing and pattern recognition (SOCPAR\u201909), pp 54\u201359","DOI":"10.1109\/SoCPaR.2009.23"},{"key":"1719_CR79","doi-asserted-by":"crossref","unstructured":"Satapathy SC, Naik A (2011) Data clustering based on teaching-learning-based optimization. In: Swarm, evolutionary, and memetic computing. Springer, Berlin, pp 148\u201356","DOI":"10.1007\/978-3-642-27242-4_18"},{"key":"1719_CR80","doi-asserted-by":"crossref","unstructured":"Sarafrazi S, Nezamabadi-pour H, Saryazdi S (2011) Disruption: a new operator in gravitational search algorithm. Scien-tia Iranica D 18(3):539\u2013548","DOI":"10.1016\/j.scient.2011.04.003"},{"issue":"10","key":"1719_CR81","doi-asserted-by":"crossref","first-page":"1003","DOI":"10.1016\/0031-3203(91)90097-O","volume":"24","author":"SZ Selim","year":"1991","unstructured":"Selim SZ, Alsultan K (1991) A simulated annealing algorithm for the clustering problem. Pattern Recognit 24(10):1003\u20131008","journal-title":"Pattern Recognit"},{"issue":"2","key":"1719_CR82","doi-asserted-by":"crossref","first-page":"187","DOI":"10.1016\/j.aca.2003.12.032","volume":"509","author":"PS Shelokar","year":"2004","unstructured":"Shelokar PS, Jayaraman VK, Kulkarni BD (2004) An ant colony approach for clustering. Analytica Chimica Acta 509(2):187\u201395","journal-title":"Analytica Chimica Acta"},{"key":"1719_CR83","doi-asserted-by":"crossref","unstructured":"Sinha AN, Das N, Sahoo G (2007) Ant colony based hybrid optimization for data clustering. Kybernetes 36(2):175\u2013191","DOI":"10.1108\/03684920710741215"},{"key":"1719_CR84","doi-asserted-by":"crossref","first-page":"201","DOI":"10.1099\/00221287-17-1-201","volume":"17","author":"P Sneath","year":"1957","unstructured":"Sneath P (1957) The application of computers to taxonomy. J Gen Microbiol 17:201\u2013226","journal-title":"J Gen Microbiol"},{"key":"1719_CR85","first-page":"1409","volume":"38","author":"R Sokal","year":"1958","unstructured":"Sokal R, Michener C (1958) A statistical method for evaluating systematic relationships. Univ Kansas Sci Bull 38:1409\u20131438","journal-title":"Univ Kansas Sci Bull"},{"key":"1719_CR86","first-page":"1","volume":"5","author":"T Sorensen","year":"1948","unstructured":"Sorensen T (1948) A method of establishing groups of equal amplitude in plant sociology based on similarity of species content and its application to analyzes of the vegetation on Danish commons. Biologiske Skrifter 5:1\u201334","journal-title":"Biologiske Skrifter"},{"key":"1719_CR87","doi-asserted-by":"crossref","unstructured":"Sung CS, Jin HW (2000) A tabu-search-based heuristic for clustering. Pattern Recognit 33(5):849\u2013858","DOI":"10.1016\/S0031-3203(99)00090-4"},{"key":"1719_CR88","doi-asserted-by":"crossref","unstructured":"Tsai CF, Tsai CW, Wu HC, Yang T (2004) ACODF: a novel data clustering approach for data mining in large databases. J Syst Softw 73(1):133\u2013145","DOI":"10.1016\/S0164-1212(03)00216-4"},{"key":"1719_CR89","doi-asserted-by":"crossref","unstructured":"Teppola P, Mujunen SP, Minkkinen P (1999) Adaptive fuzzy C-means clustering in process monitoring. In: Chemometrics and intelligent laboratory systems 45(1):23\u201328","DOI":"10.1016\/S0169-7439(98)00087-2"},{"key":"1719_CR90","doi-asserted-by":"crossref","first-page":"317","DOI":"10.1016\/S0020-0190(02)00447-7","volume":"85","author":"IC Trelea","year":"2003","unstructured":"Trelea IC (2003) The particle swarm optimization algorithm: convergence analysis and parameter selection. Inf Process Lett 85:317\u2013325","journal-title":"Inf Process Lett"},{"key":"1719_CR91","first-page":"1612","volume":"3","author":"LY Tseng","year":"1997","unstructured":"Tseng LY, Yang SB (1997) Genetic algorithms for clustering, feature selection and classification. IEEE Int Conf Neural Netw 3:1612\u20131616","journal-title":"IEEE Int Conf Neural Netw"},{"issue":"2","key":"1719_CR92","doi-asserted-by":"crossref","first-page":"415","DOI":"10.1016\/S0031-3203(00)00005-4","volume":"34","author":"LY Tseng","year":"2001","unstructured":"Tseng LY, Yang SB (2001) A genetic approach to the automatic clustering problem. Pattern Recognit 34(2):415\u2013424","journal-title":"Pattern Recognit"},{"key":"1719_CR93","unstructured":"Wang W, Yang J, Muntz R (1997) STING: a statistical information grid approach to spatial data mining. In: Proceedings of the 1997 international conference on very large data base (VLDB\u201997), Athens, Greek, pp 186\u2013195"},{"key":"1719_CR94","doi-asserted-by":"crossref","DOI":"10.1002\/0470854774","volume-title":"Statistical pattern recognition","author":"A Webb","year":"2002","unstructured":"Webb A (2002) Statistical pattern recognition. Wiley, New Jersey"},{"issue":"2","key":"1719_CR95","doi-asserted-by":"crossref","first-page":"159","DOI":"10.1023\/A:1007659514849","volume":"40","author":"GI Webb","year":"2000","unstructured":"Webb GI (2000) Multiboosting: a technique for combining boosting and wagging. Mach Learn 40(2):159\u2013196","journal-title":"Mach Learn"},{"key":"1719_CR96","doi-asserted-by":"crossref","unstructured":"Xu R, Wunsch DC (2009) Clustering. Oxford, Wiley","DOI":"10.1002\/9780470382776"},{"key":"1719_CR97","first-page":"241","volume":"97","author":"X Yan","year":"2012","unstructured":"Yan X, Zhu Y, Zou W, Wang L (2012) A new approach for data clustering using hybrid artificial bee colony algorithm. Neuro Comput 97:241\u2013250","journal-title":"Neuro Comput"},{"issue":"7","key":"1719_CR98","doi-asserted-by":"crossref","first-page":"1278","DOI":"10.1016\/j.patcog.2006.02.012","volume":"39","author":"Y Yang","year":"2006","unstructured":"Yang Y, Kamel MS (2006) An aggregated clustering approach using multi-ant colonies algorithms. Pattern Recognit 39(7):1278\u20131289","journal-title":"Pattern Recognit"},{"key":"1719_CR99","doi-asserted-by":"crossref","first-page":"338","DOI":"10.1016\/S0019-9958(65)90241-X","volume":"8","author":"L Zadeh","year":"1965","unstructured":"Zadeh L (1965) Fuzzy sets. Inf Control 8:338\u2013353","journal-title":"Inf Control"},{"key":"1719_CR100","doi-asserted-by":"crossref","unstructured":"Zhang T, Ramakrishnan R, Livny M (1996) BIRCH: an efficient data clustering method for very large databases. In: Proceedings of the ACM SIGMOD conference on management of data, pp 103\u2013114","DOI":"10.1145\/233269.233324"},{"issue":"1","key":"1719_CR101","doi-asserted-by":"crossref","first-page":"152","DOI":"10.1016\/j.patcog.2007.06.006","volume":"41","author":"H Zhou","year":"2008","unstructured":"Zhou H, Yonghuai L (2008) Accurate integration of multi-view range images using k-means clustering. Pattern Recognit 41(1):152\u2013175","journal-title":"Pattern Recognit"}],"container-title":["Soft Computing"],"original-title":[],"language":"en","link":[{"URL":"http:\/\/link.springer.com\/content\/pdf\/10.1007\/s00500-015-1719-0.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"http:\/\/link.springer.com\/article\/10.1007\/s00500-015-1719-0\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"http:\/\/link.springer.com\/content\/pdf\/10.1007\/s00500-015-1719-0","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2019,8,26]],"date-time":"2019-08-26T04:46:01Z","timestamp":1566794761000},"score":1,"resource":{"primary":{"URL":"http:\/\/link.springer.com\/10.1007\/s00500-015-1719-0"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2015,6,5]]},"references-count":101,"journal-issue":{"issue":"12","published-print":{"date-parts":[[2015,12]]}},"alternative-id":["1719"],"URL":"https:\/\/doi.org\/10.1007\/s00500-015-1719-0","relation":{},"ISSN":["1432-7643","1433-7479"],"issn-type":[{"value":"1432-7643","type":"print"},{"value":"1433-7479","type":"electronic"}],"subject":[],"published":{"date-parts":[[2015,6,5]]}}}