{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,11,4]],"date-time":"2025-11-04T15:48:32Z","timestamp":1762271312300},"reference-count":36,"publisher":"Springer Science and Business Media LLC","issue":"7","license":[{"start":{"date-parts":[[2008,11,28]],"date-time":"2008-11-28T00:00:00Z","timestamp":1227830400000},"content-version":"tdm","delay-in-days":0,"URL":"http:\/\/www.springer.com\/tdm"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Neural Comput &amp; Applic"],"published-print":{"date-parts":[[2009,10]]},"DOI":"10.1007\/s00521-008-0214-2","type":"journal-article","created":{"date-parts":[[2008,11,27]],"date-time":"2008-11-27T07:17:03Z","timestamp":1227770223000},"page":"769-779","source":"Crossref","is-referenced-by-count":14,"title":["A hybrid MPSO-BP structure adaptive algorithm for RBFNs"],"prefix":"10.1007","volume":"18","author":[{"given":"Shiwei","family":"Yu","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Kejun","family":"Zhu","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Siwei","family":"Gao","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2008,11,28]]},"reference":[{"issue":"10","key":"214_CR1","doi-asserted-by":"crossref","first-page":"2134","DOI":"10.1016\/j.compchemeng.2005.07.002","volume":"29","author":"A Shahsavand","year":"2005","unstructured":"Shahsavand A, Ahmadpour A (2005) Application of optimal RBF neural networks for optimization and characterization of porous materials. Comput Chem Eng 29(10):2134\u20132143. doi: 10.1016\/j.compchemeng.2005.07.002","journal-title":"Comput Chem Eng"},{"issue":"1","key":"214_CR2","doi-asserted-by":"crossref","first-page":"246","DOI":"10.1162\/neco.1991.3.2.246","volume":"3","author":"J Park","year":"1991","unstructured":"Park J, Sandberg IW (1991) Universal approximation using radial basis functions network. Neural Comput 3(1):246\u2013257. doi: 10.1162\/neco.1991.3.2.246","journal-title":"Neural Comput"},{"key":"214_CR3","doi-asserted-by":"crossref","unstructured":"Mu T, Asoke K Nandi, RBF neural networks for solving the inverse problem of backscattering spectra. Neural Comput Appl. doi: 10.1007\/s00521-007-0138-2","DOI":"10.1007\/s00521-007-0138-2"},{"key":"214_CR4","doi-asserted-by":"crossref","first-page":"2333","DOI":"10.1016\/j.compstruc.2004.05.014","volume":"82","author":"A Zhang","year":"2004","unstructured":"Zhang A, Zhang L (2004) RBF neural networks for the prediction of building interference effects. Comput Struc 82:2333\u20132339. doi: 10.1016\/j.compstruc.2004.05.014","journal-title":"Comput Struc"},{"issue":"3","key":"214_CR5","doi-asserted-by":"crossref","first-page":"1055","DOI":"10.1016\/j.asoc.2006.10.007","volume":"7","author":"D Ram","year":"2007","unstructured":"Ram D, Srivastava L, Pandit M, Sharma J (2007) Corrective action planning using RBF neural network. Appl Soft Comput 7(3):1055\u20131063. doi: 10.1016\/j.asoc.2006.10.007","journal-title":"Appl Soft Comput"},{"key":"214_CR6","doi-asserted-by":"crossref","unstructured":"Darken C, Moody J (1990) Fast adaptive K-means clustering: some empirical results. Proceedings of IEEE INNS international joint conference on neural networks, pp 233\u2013238","DOI":"10.1109\/IJCNN.1990.137720"},{"issue":"3","key":"214_CR7","doi-asserted-by":"crossref","first-page":"157","DOI":"10.1109\/72.363440","volume":"6","author":"C Chinrungrueng","year":"1995","unstructured":"Chinrungrueng C, Sequin CH (1995) Optimal adaptive k-means algorithm with dynamic adjustment of learning rate. IEEE Trans Neural Netw 6(3):157\u2013168. doi: 10.1109\/72.363440","journal-title":"IEEE Trans Neural Netw"},{"key":"214_CR8","volume-title":"Neural networks\u2014a comprehensive foundation","author":"S Haykin","year":"1994","unstructured":"Haykin S (1994) Neural networks\u2014a comprehensive foundation. IEEE Press, New York"},{"issue":"3","key":"214_CR9","doi-asserted-by":"crossref","first-page":"302","DOI":"10.1109\/72.80341","volume":"2","author":"S Chen","year":"1991","unstructured":"Chen S, Cowan CFN, Grant PM (1991) Orthogonal least squares learning algorithm for radial basis function networks. IEEE Trans Neural Netw 2(3):302\u2013309. doi: 10.1109\/72.80341","journal-title":"IEEE Trans Neural Netw"},{"issue":"1","key":"214_CR10","doi-asserted-by":"crossref","first-page":"195","DOI":"10.1109\/72.478404","volume":"7","author":"A Sherstinsky","year":"1996","unstructured":"Sherstinsky A, Picard RW (1996) On the efficiency of the orthogonal least squares training method for radial basis function networks. IEEE Trans Neural Netw 7(1):195\u2013200. doi: 10.1109\/72.478404","journal-title":"IEEE Trans Neural Netw"},{"key":"214_CR11","first-page":"164","volume-title":"NIPS","author":"B Hassibi","year":"1993","unstructured":"Hassibi B, Stork DG (1993) Second order derivatives for network pruning: optimal brain surgeon. In: Hanson SJ et al (eds) NIPS, vol 5. Morgan Kaufmann, Los Altos, pp 164\u2013172"},{"issue":"5","key":"214_CR12","doi-asserted-by":"crossref","first-page":"963","DOI":"10.1016\/S0893-6080(98)00051-3","volume":"11","author":"A Leonardis","year":"1998","unstructured":"Leonardis A, Bischof H (1998) An efficient MDL-based construction of RBF networks. Neural Netw 11(5):963\u2013973. doi: 10.1016\/S0893-6080(98)00051-3","journal-title":"Neural Netw"},{"issue":"6","key":"214_CR13","doi-asserted-by":"crossref","first-page":"2284","DOI":"10.1109\/TSMCB.2004.834428","volume":"34","author":"GB Huang","year":"2004","unstructured":"Huang GB, Saratchandran P, Sundararajan N (2004) An efficient sequential learning algorithm for growing and pruning RBF (GAP-RBF) networks. IEEE Trans Syst Man Cybern 34(6):2284\u20132292. doi: 10.1109\/TSMCB.2004.834428","journal-title":"IEEE Trans Syst Man Cybern"},{"key":"214_CR14","doi-asserted-by":"crossref","unstructured":"Zhang R, Huang G, Saratchandran P, Sundararajan N (2006) Improved GAP-RBF network for classification problems. Neurocomputing. doi: 10.1016\/j.neucom.2006.07.016","DOI":"10.1016\/j.neucom.2006.07.016"},{"issue":"7","key":"214_CR15","doi-asserted-by":"crossref","first-page":"1003","DOI":"10.1016\/S0893-6080(03)00052-2","volume":"16","author":"A Alexandridis","year":"2003","unstructured":"Alexandridis A, Sarimveis H, Bafas G (2003) A new algorithm for online structure and parameter adaptation of RBF networks. Neural Netw 16(7):1003\u20131017. doi: 10.1016\/S0893-6080(03)00052-2","journal-title":"Neural Netw"},{"issue":"13\u201315","key":"214_CR16","doi-asserted-by":"crossref","first-page":"1570","DOI":"10.1016\/j.neucom.2005.06.014","volume":"69","author":"A Staianoa","year":"2006","unstructured":"Staianoa A, Tagliaferria R, Pedryczb W (2006) Improving RBF networks performance in regression tasks by means of a supervised fuzzy clustering. Neurocomputing 69(13\u201315):1570\u20131581. doi: 10.1016\/j.neucom.2005.06.014","journal-title":"Neurocomputing"},{"issue":"1","key":"214_CR17","doi-asserted-by":"crossref","first-page":"2","DOI":"10.1007\/BF02312392","volume":"1","author":"B Fritzke","year":"1994","unstructured":"Fritzke B (1994) Fast learning with incremental RBF networks. Neural Process Lett 1(1):2\u20135. doi: 10.1007\/BF02312392","journal-title":"Neural Process Lett"},{"issue":"3","key":"214_CR18","doi-asserted-by":"crossref","first-page":"527","DOI":"10.1016\/S0893-6080(98)00146-4","volume":"12","author":"Q Zhu","year":"1996","unstructured":"Zhu Q, Cai Y, Liu L (1996) A global learning algorithm for a RBF network. Neural Netw 12(3):527\u2013540. doi: 10.1016\/S0893-6080(98)00146-4","journal-title":"Neural Netw"},{"issue":"6","key":"214_CR19","doi-asserted-by":"crossref","first-page":"877","DOI":"10.1016\/0893-6080(95)00029-Y","volume":"8","author":"SA Billings","year":"1995","unstructured":"Billings SA, Zheng GL (1995) Radial basis function network configuration using genetic algorithms. Neural Netw 8(6):877\u2013890. doi: 10.1016\/0893-6080(95)00029-Y","journal-title":"Neural Netw"},{"key":"214_CR20","volume-title":"Swarm intelligence","author":"J Kennedy","year":"2001","unstructured":"Kennedy J, Eberhart R, Shi YH (2001) Swarm intelligence. Morgan Kaufmann, San Francisco"},{"issue":"5","key":"214_CR21","first-page":"562","volume":"22","author":"W Liu","year":"2007","unstructured":"Liu W, Wang K (2007) Predicting chaotic time series using hybrid particle swarm optimization algorithm. Contr Decis 22(5):562\u2013565","journal-title":"Contr Decis"},{"issue":"4","key":"214_CR22","first-page":"933","volume":"20","author":"XB Li","year":"2007","unstructured":"Li XB, Liu D, Zuo L (2007) Application of RBF-PSO in nonlinear calibration for thermocouple sensor. Chin J Sens Actuators 20(4):933\u2013936","journal-title":"Chin J Sens Actuators"},{"issue":"1\u20133","key":"214_CR23","doi-asserted-by":"crossref","first-page":"241","DOI":"10.1016\/j.neucom.2006.03.007","volume":"70","author":"HM Feng","year":"2006","unstructured":"Feng HM (2006) Self-generation RBFNs using evolutional PSO learning. Neurocomputing 70(1\u20133):241\u2013251. doi: 10.1016\/j.neucom.2006.03.007","journal-title":"Neurocomputing"},{"issue":"2","key":"214_CR24","doi-asserted-by":"crossref","first-page":"326","DOI":"10.1109\/PGEC.1965.264137","volume":"14","author":"TM Cover","year":"1965","unstructured":"Cover TM (1965) Geometrical and statistical properties of systems of linear inequalities with application in pattern recognition. IEEE Trans Electron Comput EC 14(2):326\u2013334. doi: 10.1109\/PGEC.1965.264136","journal-title":"IEEE Trans Electron Comput EC"},{"key":"214_CR25","first-page":"321","volume":"2","author":"DS Broomhead","year":"1988","unstructured":"Broomhead DS, Lowe D (1988) Multivariable functional interpolation and adaptive networks. Complex Syst 2:321\u2013355","journal-title":"Complex Syst"},{"issue":"3","key":"214_CR26","doi-asserted-by":"crossref","first-page":"657","DOI":"10.1109\/72.761725","volume":"10","author":"NB Karayiannis","year":"1999","unstructured":"Karayiannis NB (1999) Reformulated radial basis neural networks trained by gradient descent. IEEE Trans Neural Netw 10(3):657\u2013671. doi: 10.1109\/72.761725","journal-title":"IEEE Trans Neural Netw"},{"issue":"3","key":"214_CR27","doi-asserted-by":"crossref","first-page":"281","DOI":"10.1162\/neco.1989.1.2.281","volume":"1","author":"J Moody","year":"1989","unstructured":"Moody J, Darken C (1989) Faster learning in networks of locally tuned processing units. Neural Comput 1(3):281\u2013294. doi: 10.1162\/neco.1989.1.2.281","journal-title":"Neural Comput"},{"key":"214_CR28","volume-title":"Neural networks: a comprehensive foundation","author":"S Haykin","year":"1999","unstructured":"Haykin S (1999) Neural networks: a comprehensive foundation, 2nd edn. Prentice Hall, New Jersey","edition":"2"},{"key":"214_CR29","first-page":"1942","volume":"IV","author":"R Eberhart","year":"1995","unstructured":"Eberhart R, Kennedy J (1995) Particle swarm optimization. IEEE Int Conf Neural Netw IV:1942\u20131947","journal-title":"IEEE Int Conf Neural Netw"},{"key":"214_CR30","doi-asserted-by":"crossref","unstructured":"Clerc M (1999) The swarm and the queen: towards a deterministic and adaptive particle swarm optimization. In: Proceeding congress on evolutionary computation, Washington DC, pp 1951\u20131957","DOI":"10.1109\/CEC.1999.785513"},{"key":"214_CR31","doi-asserted-by":"crossref","unstructured":"Shi YH, Eberhart R (1998) A modified particle swarm optimizer. In: IEEE international conference on evolutionary computation, pp 69\u201373","DOI":"10.1109\/ICEC.1998.699146"},{"key":"214_CR32","doi-asserted-by":"crossref","unstructured":"Kennedy J, Eberhart R (1997) A discrete binary version of the particle swarm algorithm. In: Proceedings of the World multiconference on systemic, cybernetics and informatics, Piscataway, NJ, pp 4104\u20134109","DOI":"10.1109\/ICSMC.1997.637339"},{"issue":"6","key":"214_CR33","doi-asserted-by":"crossref","first-page":"686","DOI":"10.1109\/3477.809024","volume":"29","author":"CC Wong","year":"1999","unstructured":"Wong CC, Chen CC (1999) A hybrid clustering and gradient descent approach for fuzzy modeling. IEEE Trans Syst Man Cybern 29(6):686\u2013693","journal-title":"IEEE Trans Syst Man Cybern"},{"issue":"2","key":"214_CR34","doi-asserted-by":"crossref","first-page":"4","DOI":"10.1109\/72.80202","volume":"1","author":"KS Narendra","year":"1990","unstructured":"Narendra KS, Parthasarathy K (1990) Identification and control of dynamical systems using neural networks. IEEE Trans Neural Netw 1(2):4\u201327. doi: 10.1109\/72.80202","journal-title":"IEEE Trans Neural Netw"},{"issue":"9","key":"214_CR35","doi-asserted-by":"crossref","first-page":"1645","DOI":"10.1016\/S0893-6080(98)00100-2","volume":"11","author":"GP Liu","year":"1998","unstructured":"Liu GP, Kadirkamanathan V, Billings SA (1998) Online identification of nonlinear systems using Volterra polynomial basis function neural networks. Neural Netw 11(9):1645\u20131657. doi: 10.1016\/S0893-6080(98)00100-2","journal-title":"Neural Netw"},{"key":"214_CR36","unstructured":"Machine Learning Repository UCI. http:\/\/www.ics.uci.edu\/_mlearn\/MLRepository.html"}],"container-title":["Neural Computing and Applications"],"original-title":[],"language":"en","link":[{"URL":"http:\/\/link.springer.com\/content\/pdf\/10.1007\/s00521-008-0214-2.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"http:\/\/link.springer.com\/article\/10.1007\/s00521-008-0214-2\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"http:\/\/link.springer.com\/content\/pdf\/10.1007\/s00521-008-0214-2","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2019,5,29]],"date-time":"2019-05-29T02:06:57Z","timestamp":1559095617000},"score":1,"resource":{"primary":{"URL":"http:\/\/link.springer.com\/10.1007\/s00521-008-0214-2"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2008,11,28]]},"references-count":36,"journal-issue":{"issue":"7","published-print":{"date-parts":[[2009,10]]}},"alternative-id":["214"],"URL":"https:\/\/doi.org\/10.1007\/s00521-008-0214-2","relation":{},"ISSN":["0941-0643","1433-3058"],"issn-type":[{"value":"0941-0643","type":"print"},{"value":"1433-3058","type":"electronic"}],"subject":[],"published":{"date-parts":[[2008,11,28]]}}}