{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2024,4,28]],"date-time":"2024-04-28T11:54:21Z","timestamp":1714305261793},"reference-count":40,"publisher":"Springer Science and Business Media LLC","issue":"3","license":[{"start":{"date-parts":[[2019,5,15]],"date-time":"2019-05-15T00:00:00Z","timestamp":1557878400000},"content-version":"tdm","delay-in-days":0,"URL":"http:\/\/www.springer.com\/tdm"},{"start":{"date-parts":[[2019,5,15]],"date-time":"2019-05-15T00:00:00Z","timestamp":1557878400000},"content-version":"vor","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":[[2020,2]]},"DOI":"10.1007\/s00500-019-04058-4","type":"journal-article","created":{"date-parts":[[2019,5,15]],"date-time":"2019-05-15T22:30:59Z","timestamp":1557959459000},"page":"2265-2285","update-policy":"http:\/\/dx.doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":1,"title":["A novel parallel object-tracking behavior algorithm based on dynamics for data clustering"],"prefix":"10.1007","volume":"24","author":[{"given":"Xiang","family":"Feng","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Zhaolin","family":"Lai","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Huiqun","family":"Yu","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2019,5,15]]},"reference":[{"key":"4058_CR1","first-page":"1","volume":"1","author":"LM Abualigah","year":"2017","unstructured":"Abualigah LM, Khader AT (2017) Unsupervised text feature selection technique based on hybrid particle swarm optimization algorithm with genetic operators for the text clustering. J Supercomput 1:1\u201323","journal-title":"J Supercomput"},{"key":"4058_CR2","doi-asserted-by":"publisher","first-page":"423","DOI":"10.1016\/j.asoc.2017.06.059","volume":"60","author":"LM Abualigah","year":"2017","unstructured":"Abualigah LM, Khader AT, Al-Betar MA, Gandomi AH (2017) A novel hybridization strategy for krill herd algorithm applied to clustering techniques. Appl Soft Comput 60:423\u2013435","journal-title":"Appl Soft Comput"},{"key":"4058_CR3","first-page":"1","volume":"5","author":"LM Abualigah","year":"2018","unstructured":"Abualigah LM, Khader AT, Hanandeh ES (2018) Hybrid clustering analysis using improved krill herd algorithm. Appl Intell 5:1\u201325","journal-title":"Appl Intell"},{"issue":"1\u20132","key":"4058_CR4","doi-asserted-by":"publisher","first-page":"199","DOI":"10.1007\/s00170-009-1958-2","volume":"45","author":"B Amiri","year":"2009","unstructured":"Amiri B, Fathian M, Maroosi A (2009) Removed: application of shuffled frog-leaping algorithm on clustering. Int J Adv Manuf Technol 45(1\u20132):199\u2013209","journal-title":"Int J Adv Manuf Technol"},{"key":"4058_CR5","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-642-04005-4_2","volume-title":"Review of clustering algorithms","author":"WA Barbakh","year":"2009","unstructured":"Barbakh WA, Wu Y, Fyfe C (2009) Review of clustering algorithms. Springer, Berlin"},{"issue":"1","key":"4058_CR6","doi-asserted-by":"publisher","first-page":"145","DOI":"10.1016\/j.patcog.2010.07.006","volume":"44","author":"N Bassiou","year":"2011","unstructured":"Bassiou N, Kotropoulos C (2011) Long distance bigram models applied to word clustering. Pattern Recognit 44(1):145\u2013158","journal-title":"Pattern Recognit"},{"key":"4058_CR7","doi-asserted-by":"publisher","DOI":"10.1016\/j.patrec.2013.11.012","volume-title":"Weighted ensemble of algorithms for complex data clustering","author":"V Berikov","year":"2014","unstructured":"Berikov V (2014) Weighted ensemble of algorithms for complex data clustering. Elsevier Science Inc., Amsterdam"},{"issue":"12","key":"4058_CR8","doi-asserted-by":"publisher","first-page":"11243","DOI":"10.1016\/j.eswa.2012.03.046","volume":"39","author":"CJ Carmona","year":"2012","unstructured":"Carmona CJ, Ram\u0142rez-Gallego S, Torres F, Bernal E, Del Jesus MJ, Garc\u0142a S (2012) Web usage mining to improve the design of an e-commerce website: Orolivesur.com. Expert Syst Appl 39(12):11243\u201311249","journal-title":"Expert Syst Appl"},{"issue":"2","key":"4058_CR9","doi-asserted-by":"publisher","first-page":"191","DOI":"10.1109\/TCYB.2014.2322602","volume":"45","author":"R Cheng","year":"2015","unstructured":"Cheng R, Jin Y (2015) A competitive swarm optimizer for large scale optimization. IEEE Trans Cybern 45(2):191","journal-title":"IEEE Trans Cybern"},{"issue":"5","key":"4058_CR10","doi-asserted-by":"publisher","first-page":"e1603041","DOI":"10.1126\/sciadv.1603041","volume":"3","author":"DD Chin","year":"2017","unstructured":"Chin DD, Lentink D (2017) How birds direct impulse to minimize the energetic cost of foraging flight. Sci Adv 3(5):e1603041","journal-title":"Sci Adv"},{"issue":"1","key":"4058_CR11","doi-asserted-by":"publisher","first-page":"1582","DOI":"10.1016\/j.eswa.2011.07.123","volume":"39","author":"T Cura","year":"2012","unstructured":"Cura T (2012) A particle swarm optimization approach to clustering. Expert Syst Appl 39(1):1582\u20131588","journal-title":"Expert Syst Appl"},{"issue":"1","key":"4058_CR12","doi-asserted-by":"publisher","first-page":"3","DOI":"10.1016\/j.swevo.2011.02.002","volume":"1","author":"J Derrac","year":"2011","unstructured":"Derrac J, Garc\u0142a 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"},{"issue":"6130","key":"4058_CR13","doi-asserted-by":"publisher","first-page":"317","DOI":"10.1126\/science.1236180","volume":"340","author":"MS Donovan","year":"2013","unstructured":"Donovan MS (2013) Generating improvement through research and development in education systems. Science 340(6130):317\u2013319","journal-title":"Science"},{"key":"4058_CR14","doi-asserted-by":"publisher","first-page":"114","DOI":"10.1016\/j.engappai.2014.07.016","volume":"36","author":"MB Dowlatshahi","year":"2014","unstructured":"Dowlatshahi MB, Nezamabadi-Pour H (2014) Ggsa: a grouping gravitational search algorithm for data clustering. Eng Appl Artif Intell 36:114\u2013121","journal-title":"Eng Appl Artif Intell"},{"issue":"7547","key":"4058_CR15","doi-asserted-by":"publisher","first-page":"345","DOI":"10.1038\/nature14106","volume":"520","author":"JE Dunsmoor","year":"2015","unstructured":"Dunsmoor JE, Murty VP, Davachi L, Phelps EA (2015) Emotional learning selectively and retroactively strengthens memories for related events. Nature 520(7547):345","journal-title":"Nature"},{"issue":"2","key":"4058_CR16","doi-asserted-by":"publisher","first-page":"87","DOI":"10.1016\/j.ins.2012.12.053","volume":"233","author":"X Feng","year":"2013","unstructured":"Feng X, Lau FCM, Yu H (2013) A novel bio-inspired approach based on the behavior of mosquitoes. Inf Sci 233(2):87\u2013108","journal-title":"Inf Sci"},{"issue":"99","key":"4058_CR17","first-page":"1","volume":"PP","author":"X Feng","year":"2017","unstructured":"Feng X, Wang Y, Yu H, Luo F (2017) A novel intelligence algorithm based on the social group optimization behaviors. IEEE Trans Syst Man Cybern Syst PP(99):1\u201312","journal-title":"IEEE Trans Syst Man Cybern Syst"},{"issue":"3","key":"4058_CR18","doi-asserted-by":"publisher","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(3):175\u2013184","journal-title":"Inf Sci"},{"key":"4058_CR19","doi-asserted-by":"crossref","unstructured":"Hatamlou A, Abdullah S, Nezamabadi-Pour H (2011) Application of gravitational search algorithm on data clustering. In: International conference on rough sets and knowledge technology, pp 337\u2013346","DOI":"10.1007\/978-3-642-24425-4_44"},{"issue":"2","key":"4058_CR20","doi-asserted-by":"publisher","first-page":"133","DOI":"10.1109\/TSMCC.2008.2007252","volume":"39","author":"ER Hruschka","year":"2009","unstructured":"Hruschka ER, Campello RJGB, Freitas AA (2009) A survey of evolutionary algorithms for clustering. IEEE Trans Syst Man Cybern Part C 39(2):133\u2013155","journal-title":"IEEE Trans Syst Man Cybern Part C"},{"key":"4058_CR21","volume-title":"Data clustering: 50 years beyond k-means","author":"AK Jain","year":"2008","unstructured":"Jain AK (2008) Data clustering: 50 years beyond k-means. Springer, Berlin"},{"issue":"11","key":"4058_CR22","doi-asserted-by":"publisher","first-page":"3134","DOI":"10.1016\/j.cnsns.2013.03.011","volume":"18","author":"B Jiang","year":"2013","unstructured":"Jiang B, Wang N, Wang L (2013) Particle swarm optimization with age-group topology for multimodal functions and data clustering. Commun Nonlinear Sci Numer Simul 18(11):3134\u20133145","journal-title":"Commun Nonlinear Sci Numer Simul"},{"issue":"7","key":"4058_CR23","doi-asserted-by":"publisher","first-page":"3204","DOI":"10.1016\/j.eswa.2013.11.018","volume":"41","author":"S Jun","year":"2014","unstructured":"Jun S, Park SS, Jang DS (2014) Document clustering method using dimension reduction and support vector clustering to overcome sparseness. Expert Syst Appl 41(7):3204\u20133212","journal-title":"Expert Syst Appl"},{"issue":"3","key":"4058_CR24","doi-asserted-by":"publisher","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. Expert Syst Appl 34(3):1754\u20131762","journal-title":"Expert Syst Appl"},{"issue":"1","key":"4058_CR25","doi-asserted-by":"publisher","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(1):652\u2013657","journal-title":"Appl Soft Comput"},{"issue":"13","key":"4058_CR26","doi-asserted-by":"publisher","first-page":"6009","DOI":"10.1016\/j.eswa.2014.03.021","volume":"41","author":"G Krishnasamy","year":"2014","unstructured":"Krishnasamy G, Kulkarni AJ, Paramesran R (2014) A hybrid approach for data clustering based on modified cohort intelligence and k-means. Expert Syst Appl 41(13):6009\u20136016","journal-title":"Expert Syst Appl"},{"key":"4058_CR27","first-page":"1","volume":"14","author":"PS Mann","year":"2017","unstructured":"Mann PS, Singh S (2017) Improved artificial bee colony metaheuristic for energy-efficient clustering in wireless sensor networks. Artif Intell Rev 14:1\u201326","journal-title":"Artif Intell Rev"},{"issue":"6","key":"4058_CR28","doi-asserted-by":"publisher","first-page":"617","DOI":"10.1007\/s10732-008-9080-4","volume":"15","author":"D Molina","year":"2009","unstructured":"Molina D, Lozano M, Herrera F (2009) A study on the use of non-parametric tests for analyzing the evolutionary algorithms\u2019 behaviour: a case study on the cec\u20192005 special session on real parameter optimization. J Heuristics 15(6):617\u2013644","journal-title":"J Heuristics"},{"key":"4058_CR29","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1016\/j.swevo.2013.11.003","volume":"16","author":"SJ Nanda","year":"2014","unstructured":"Nanda SJ, Panda G (2014) A survey on nature inspired metaheuristic algorithms for partitional clustering. Swarm Evol Comput 16:1\u201318","journal-title":"Swarm Evol Comput"},{"issue":"1","key":"4058_CR30","doi-asserted-by":"publisher","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 J 10(1):183\u2013197","journal-title":"Appl Soft Comput J"},{"issue":"4","key":"4058_CR31","doi-asserted-by":"publisher","first-page":"1492","DOI":"10.1016\/j.eswa.2013.08.046","volume":"41","author":"NM Portela","year":"2014","unstructured":"Portela NM, Cavalcanti GDC, Ren TI (2014) Semi-supervised clustering for mr brain image segmentation. Expert Syst Appl 41(4):1492\u20131497","journal-title":"Expert Syst Appl"},{"issue":"3","key":"4058_CR32","doi-asserted-by":"publisher","first-page":"211","DOI":"10.1007\/s10462-010-9191-9","volume":"35","author":"S Rana","year":"2011","unstructured":"Rana S, Jasola S, Kumar R (2011) A review on particle swarm optimization algorithms and their applications to data clustering. Artif Intell Rev 35(3):211\u2013222","journal-title":"Artif Intell Rev"},{"key":"4058_CR33","doi-asserted-by":"publisher","first-page":"58","DOI":"10.1016\/j.swevo.2016.01.002","volume":"28","author":"A Sharma","year":"2016","unstructured":"Sharma A, Sharma A, Panigrahi BK, Kiran D, Kumar R (2016) Ageist spider monkey optimization algorithm. Swarm Evol Comput 28:58\u201377","journal-title":"Swarm Evol Comput"},{"key":"4058_CR34","unstructured":"Shopon M, Adnan MA, Mridha MF (2017) Krill herd based clustering algorithm for wireless sensor networks. In: International workshop on computational intelligence, pp 96\u2013100"},{"key":"4058_CR35","doi-asserted-by":"publisher","first-page":"782","DOI":"10.1016\/j.ins.2015.09.056","volume":"329","author":"G Squillero","year":"2017","unstructured":"Squillero G, Tonda AP (2017) Divergence of character and premature convergence: a survey of methodologies for promoting diversity in evolutionary optimization. Inf Sci 329:782\u2013799","journal-title":"Inf Sci"},{"key":"4058_CR36","unstructured":"Van der Merwe DW, Engelbrecht AP (2004) Data clustering using particle swarm optimization. In: The 2003 congress on evolutionary computation, vol 1, 2003. CEC \u201903. pp 215\u2013220"},{"issue":"9","key":"4058_CR37","doi-asserted-by":"publisher","first-page":"1202","DOI":"10.1109\/TSMC.2015.2503406","volume":"46","author":"Z Wang","year":"2016","unstructured":"Wang Z, Lu R, Chen D, Zou F (2016) An experience information teaching\u2013clearning-based optimization for global optimization. IEEE Trans Syst Man Cybern Syst 46(9):1202\u20131214","journal-title":"IEEE Trans Syst Man Cybern Syst"},{"key":"4058_CR38","doi-asserted-by":"publisher","first-page":"144","DOI":"10.1016\/j.neucom.2015.01.058","volume":"158","author":"WL Xiang","year":"2015","unstructured":"Xiang WL, Zhu N, Ma SF, Meng XL, An MQ (2015) A dynamic shuffled differential evolution algorithm for data clustering. Neurocomputing 158:144\u2013154","journal-title":"Neurocomputing"},{"issue":"1","key":"4058_CR39","doi-asserted-by":"publisher","first-page":"241","DOI":"10.1016\/j.neucom.2012.04.025","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. Neurocomputing 97(1):241\u2013250","journal-title":"Neurocomputing"},{"issue":"6","key":"4058_CR40","doi-asserted-by":"publisher","first-page":"1144","DOI":"10.1109\/TSMCA.2011.2113334","volume":"41","author":"CC Yang","year":"2011","unstructured":"Yang CC, Ng TD (2011) Analyzing and visualizing web opinion development and social interactions with density-based clustering. IEEE Trans Syst Man Cybern Part A Syst Hum 41(6):1144\u20131155","journal-title":"IEEE Trans Syst Man Cybern Part A Syst Hum"}],"container-title":["Soft Computing"],"original-title":[],"language":"en","link":[{"URL":"http:\/\/link.springer.com\/content\/pdf\/10.1007\/s00500-019-04058-4.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"http:\/\/link.springer.com\/article\/10.1007\/s00500-019-04058-4\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"http:\/\/link.springer.com\/content\/pdf\/10.1007\/s00500-019-04058-4.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2020,5,13]],"date-time":"2020-05-13T23:24:22Z","timestamp":1589412262000},"score":1,"resource":{"primary":{"URL":"http:\/\/link.springer.com\/10.1007\/s00500-019-04058-4"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2019,5,15]]},"references-count":40,"journal-issue":{"issue":"3","published-print":{"date-parts":[[2020,2]]}},"alternative-id":["4058"],"URL":"https:\/\/doi.org\/10.1007\/s00500-019-04058-4","relation":{},"ISSN":["1432-7643","1433-7479"],"issn-type":[{"value":"1432-7643","type":"print"},{"value":"1433-7479","type":"electronic"}],"subject":[],"published":{"date-parts":[[2019,5,15]]},"assertion":[{"value":"15 May 2019","order":1,"name":"first_online","label":"First Online","group":{"name":"ArticleHistory","label":"Article History"}},{"order":1,"name":"Ethics","group":{"name":"EthicsHeading","label":"Compliance with ethical standards"}},{"value":"The authors declare that they have no conflict of interest. This article does not contain any studies with human participants or animals performed by any of the authors. Informed consent was obtained from all individual participants included in the study.","order":2,"name":"Ethics","group":{"name":"EthicsHeading","label":"Conflict of interest"}}]}}