{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,9]],"date-time":"2026-03-09T21:50:19Z","timestamp":1773093019565,"version":"3.50.1"},"reference-count":30,"publisher":"Springer Science and Business Media LLC","issue":"1","license":[{"start":{"date-parts":[[2016,11,17]],"date-time":"2016-11-17T00:00:00Z","timestamp":1479340800000},"content-version":"unspecified","delay-in-days":0,"URL":"http:\/\/www.springer.com\/tdm"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["Neural Comput &amp; Applic"],"published-print":{"date-parts":[[2018,7]]},"DOI":"10.1007\/s00521-016-2686-9","type":"journal-article","created":{"date-parts":[[2016,11,17]],"date-time":"2016-11-17T11:43:57Z","timestamp":1479383037000},"page":"271-287","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":66,"title":["Social group optimization for global optimization of multimodal functions and data clustering problems"],"prefix":"10.1007","volume":"30","author":[{"given":"Anima","family":"Naik","sequence":"first","affiliation":[]},{"given":"Suresh Chandra","family":"Satapathy","sequence":"additional","affiliation":[]},{"given":"Amira S.","family":"Ashour","sequence":"additional","affiliation":[]},{"given":"Nilanjan","family":"Dey","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2016,11,17]]},"reference":[{"issue":"2","key":"2686_CR1","doi-asserted-by":"crossref","first-page":"376","DOI":"10.1016\/j.amc.2009.01.009","volume":"210","author":"A Ahrari","year":"2009","unstructured":"Ahrari A, Shariat-Panahi M, Atai AA (2009) GEM: a novel evolutionary optimization method with improved neighborhood search. Appl Math Comput 210(2):376\u2013386","journal-title":"Appl Math Comput"},{"key":"2686_CR2","doi-asserted-by":"crossref","unstructured":"Yin X, Germay N (1993) A fast genetic algorithm with sharing scheme using cluster analysis methods in multimodal function optimization. In: Proceedings of the international conference on artificial neural networks and genetic algorithms, pp 450\u2013457","DOI":"10.1007\/978-3-7091-7533-0_65"},{"issue":"3","key":"2686_CR3","doi-asserted-by":"crossref","first-page":"207","DOI":"10.1162\/106365602760234081","volume":"10","author":"JP Li","year":"2002","unstructured":"Li JP, Balazs ME, Parks GT, Clarkson PJ (2002) A species conserving genetic algorithm for multimodal function optimization. Evolut Comput 10(3):207\u2013234","journal-title":"Evolut Comput"},{"issue":"2","key":"2686_CR4","doi-asserted-by":"crossref","first-page":"2017","DOI":"10.1016\/j.asoc.2010.06.017","volume":"11","author":"Y Liang","year":"2011","unstructured":"Liang Y, Leung KS (2011) Genetic Algorithm with adaptive elitist-population strategies for multimodal function optimization. Appl Soft Comput J 11(2):2017\u20132034","journal-title":"Appl Soft Comput J"},{"issue":"1465","key":"2686_CR5","doi-asserted-by":"crossref","first-page":"5","DOI":"10.1098\/rstb.2005.1733","volume":"361","author":"D Sumper","year":"2006","unstructured":"Sumper D (2006) The principles of collective animal behaviour. Philos Trans R Soc B 361(1465):5\u201322","journal-title":"Philos Trans R Soc B"},{"issue":"1\u20132","key":"2686_CR6","doi-asserted-by":"crossref","first-page":"49","DOI":"10.1016\/j.mbs.2008.06.003","volume":"214","author":"A Kolpas","year":"2008","unstructured":"Kolpas A, Moehlis J, Frewen TA, Kevrekidis IG (2008) Coarse analysis of collective motion with different communication mechanisms. Math Biosci 214(1\u20132):49\u201357","journal-title":"Math Biosci"},{"issue":"3","key":"2686_CR7","doi-asserted-by":"crossref","first-page":"281","DOI":"10.1109\/TEVC.2005.857610","volume":"10","author":"JJ Liang","year":"2006","unstructured":"Liang JJ, Qin AK, Suganthan PN, Baskar S (2006) Comprehensive learning particle swarm optimizer for global optimization of multimodal functions. IEEE Trans Evolut Comput 10(3):281\u2013295","journal-title":"IEEE Trans Evolut Comput"},{"issue":"1","key":"2686_CR8","doi-asserted-by":"crossref","first-page":"39","DOI":"10.1016\/j.asoc.2008.03.001","volume":"9","author":"DB Chen","year":"2009","unstructured":"Chen DB, Zhao CX (2009) Particle swarm optimization with adaptive population size and its application. Appl Soft Comput J 9(1):39\u201348","journal-title":"Appl Soft Comput J"},{"key":"2686_CR9","doi-asserted-by":"crossref","unstructured":"RC Eberhart, J Kennedy (1995) A new optimizer using particle swarm theory. In Proceedings of the 6th international symposium micromachine human science, Nagoya, pp 39\u201343","DOI":"10.1109\/MHS.1995.494215"},{"key":"2686_CR10","doi-asserted-by":"crossref","unstructured":"Shi Y, Eberhart RC (1998) A modified particle swarm optimizer. In: Proceedings of IEEE congress on evolutionary computation, pp 69\u201373","DOI":"10.1109\/ICEC.1998.699146"},{"issue":"1","key":"2686_CR11","doi-asserted-by":"crossref","first-page":"58","DOI":"10.1109\/4235.985692","volume":"6","author":"M Clerc","year":"2000","unstructured":"Clerc M, Kennedy J (2000) The particle swarm-explosion, stability, and convergence in a multidimensional complex space. IEEE Trans Evol Comput 6(1):58\u201373","journal-title":"IEEE Trans Evol Comput"},{"key":"2686_CR12","doi-asserted-by":"crossref","unstructured":"Kennedy J, Mendes R (2002) Population structure and particle swarm performance. In: Proceedings of IEEE congress on evolutionary computation, Honolulu, pp 1671\u20131676","DOI":"10.1109\/CEC.2002.1004493"},{"key":"2686_CR13","unstructured":"Parsopoulos KE, Vrahatis MN (2004) UPSO\u2014a unified particle swarm optimization scheme. In: Lecture series on computational sciences, pp 868\u2013873"},{"key":"2686_CR14","doi-asserted-by":"crossref","first-page":"204","DOI":"10.1109\/TEVC.2004.826074","volume":"8","author":"R Mendes","year":"2004","unstructured":"Mendes R, Kennedy J, Neves J (2004) The fully informed particle swarm: simpler, maybe better. IEEE Trans Evol Comput 8:204\u2013210","journal-title":"IEEE Trans Evol Comput"},{"key":"2686_CR15","doi-asserted-by":"crossref","unstructured":"Peram T, Veeramachaneni K, Mohan CK (2003) Fitness-distance-ratio based particle swarm optimization. In: Proceedings of the IEEE swarm intelligence symposium, pp 174\u2013181","DOI":"10.1109\/SIS.2003.1202264"},{"issue":"3","key":"2686_CR16","doi-asserted-by":"crossref","first-page":"281","DOI":"10.1109\/TEVC.2005.857610","volume":"10","author":"JJ Liang","year":"2006","unstructured":"Liang JJ, Qin AK, Suganthan PN, Baskar S (2006) Comprehensive learning particle swarm optimizer for global optimization of multimodal functions. IEEE Trans Evol Comput 10(3):281\u2013295","journal-title":"IEEE Trans Evol Comput"},{"key":"2686_CR17","doi-asserted-by":"publisher","DOI":"10.1007\/s40747-016-0022-8","author":"SC Satapathy","year":"2016","unstructured":"Satapathy SC, Naik A (2016) Social group optimization (SGO): a new population evolutionary optimization technique. J Complex Intell Syst. doi: 10.1007\/s40747-016-0022-8","journal-title":"J Complex Intell Syst"},{"key":"2686_CR18","doi-asserted-by":"crossref","first-page":"263","DOI":"10.1016\/0303-2647(96)01621-8","volume":"39","author":"R Salomon","year":"1996","unstructured":"Salomon R (1996) Reevaluating genetic algorithm performance under coordinate rotation of benchmark functions. BioSystems 39:263\u2013278","journal-title":"BioSystems"},{"key":"2686_CR19","doi-asserted-by":"crossref","unstructured":"Naik A, Satapathy SC, Parvathi K (2013) A comparative analysis of results of data clustering with variants of particle swarm optimization. In: International conference on swarm, evolutionary, and Memetic computing, pp 180\u2013192","DOI":"10.1007\/978-3-319-03756-1_16"},{"key":"2686_CR20","unstructured":"Mertz CJ, Blake CL. UCI repository of machine learning databases. http:\/\/www.ics.uci.edu\/~mlearn\/MLRepository.html"},{"key":"2686_CR21","unstructured":"Virmani J, Dey N, Kumar V (2016) PCA-PNN and PCA-SVM based CAD systems for breast density classification. In: Applications of intelligent optimization in biology and medicine, Springer, New York, pp 159\u2013180"},{"issue":"3","key":"2686_CR22","doi-asserted-by":"crossref","first-page":"384","DOI":"10.1166\/jmihi.2014.1265","volume":"4","author":"N Dey","year":"2014","unstructured":"Dey N, Samanta S, Chakraborty S, Das A, Chaudhuri SS, Suri JS (2014) Firefly algorithm for optimization of scaling factors during embedding of manifold medical information: an application in ophthalmology imaging. J Med Imaging Health Inform 4(3):384\u2013394","journal-title":"J Med Imaging Health Inform"},{"key":"2686_CR23","doi-asserted-by":"publisher","DOI":"10.1007\/s00521-016-2267-y","author":"R Kumar","year":"2016","unstructured":"Kumar R, Rajan A, Talukdar FA, Dey N, Santhi V, Balas VE (2016) Optimization of 5.5-GHz CMOS LNA parameters using firefly algorithm. Neural Comput Appl. doi: 10.1007\/s00521-016-2267-y","journal-title":"Neural Comput Appl"},{"issue":"03","key":"2686_CR24","first-page":"244","volume":"6","author":"AS Ashour","year":"2015","unstructured":"Ashour AS, Samanta S, Dey N, Kausar N, Abdessalemkaraa WB, Hassanien AE (2015) Computed tomography image enhancement using cuckoo search: a log transform based approach. J Signal Inf Process 6(03):244","journal-title":"J Signal Inf Process"},{"issue":"1","key":"2686_CR25","doi-asserted-by":"crossref","first-page":"60","DOI":"10.3390\/jimaging1010060","volume":"1","author":"N Dey","year":"2015","unstructured":"Dey N, Ashour AS, Beagum S, Pistola DS, Gospodinov M, Gospodinova EP, Tavares JM (2015) Parameter optimization for local polynomial approximation based intersection confidence interval filter using genetic algorithm: an application for brain MRI image de-noising. J Imaging 1(1):60\u201384","journal-title":"J Imaging"},{"key":"2686_CR26","doi-asserted-by":"crossref","unstructured":"Cheriguene S, Azizi N, Zemmal N, Dey N, Djellali H, Farah N (2016) Optimized tumor breast cancer classification using combining random subspace and static classifiers selection paradigms. In: Applications of intelligent optimization in biology and medicine. Springer, New York, pp 289\u2013307","DOI":"10.1007\/978-3-319-21212-8_13"},{"key":"2686_CR27","doi-asserted-by":"crossref","unstructured":"Kausar N, Palaniappan S, Samir BB, Abdullah A, Dey N (2016) Systematic analysis of applied data mining based optimization algorithms in clinical attribute extraction and classification for diagnosis of cardiac patients. In: Hassanien AE, Grosan C, Tolba MF (eds) Applications of intelligent optimization in biology and medicine. Springer, New York, pp 217\u2013231","DOI":"10.1007\/978-3-319-21212-8_9"},{"issue":"5","key":"2686_CR28","doi-asserted-by":"crossref","first-page":"315","DOI":"10.1504\/IJBIC.2013.057193","volume":"5","author":"N Dey","year":"2013","unstructured":"Dey N, Samanta S, Yang X-S, Das A, Chaudhuri SS (2013) Optimisation of scaling factors in electrocardiogram signal watermarking using cuckoo search. Int J Bio-Inspired Comput 5(5):315\u2013326","journal-title":"Int J Bio-Inspired Comput"},{"issue":"2","key":"2686_CR29","first-page":"18","volume":"6","author":"J Kaliannan","year":"2015","unstructured":"Kaliannan J, Baskaran A, Dey N (2015) Automatic generation control of Thermal\u2013Thermal-Hydro power systems with PID controller using ant colony optimization. Int J Serv Sci Manag Eng Technol 6(2):18\u201334","journal-title":"Int J Serv Sci Manag Eng Technol"},{"key":"2686_CR30","doi-asserted-by":"crossref","unstructured":"Chakraborty S, Samanta S, Biswas D, Dey N, Chaudhuri SS (2013) Particle swarm optimization based parameter optimization technique in medical information hiding. In: 2013 IEEE international conference on computational intelligence and computing research (ICCIC), pp 1\u20136","DOI":"10.1109\/ICCIC.2013.6724173"}],"container-title":["Neural Computing and Applications"],"original-title":[],"language":"en","link":[{"URL":"http:\/\/link.springer.com\/article\/10.1007\/s00521-016-2686-9\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"http:\/\/link.springer.com\/content\/pdf\/10.1007\/s00521-016-2686-9.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"http:\/\/link.springer.com\/content\/pdf\/10.1007\/s00521-016-2686-9.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2020,9,27]],"date-time":"2020-09-27T10:32:33Z","timestamp":1601202753000},"score":1,"resource":{"primary":{"URL":"http:\/\/link.springer.com\/10.1007\/s00521-016-2686-9"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2016,11,17]]},"references-count":30,"journal-issue":{"issue":"1","published-print":{"date-parts":[[2018,7]]}},"alternative-id":["2686"],"URL":"https:\/\/doi.org\/10.1007\/s00521-016-2686-9","relation":{},"ISSN":["0941-0643","1433-3058"],"issn-type":[{"value":"0941-0643","type":"print"},{"value":"1433-3058","type":"electronic"}],"subject":[],"published":{"date-parts":[[2016,11,17]]}}}