{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,17]],"date-time":"2026-04-17T23:51:57Z","timestamp":1776469917314,"version":"3.51.2"},"reference-count":42,"publisher":"Springer Science and Business Media LLC","issue":"6","license":[{"start":{"date-parts":[[2014,6,10]],"date-time":"2014-06-10T00:00:00Z","timestamp":1402358400000},"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":["Neural Comput &amp; Applic"],"published-print":{"date-parts":[[2014,11]]},"DOI":"10.1007\/s00521-014-1627-8","type":"journal-article","created":{"date-parts":[[2014,6,10]],"date-time":"2014-06-10T18:39:00Z","timestamp":1402425540000},"page":"1407-1422","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":68,"title":["A hybridization of teaching\u2013learning-based optimization and differential evolution for chaotic time series prediction"],"prefix":"10.1007","volume":"25","author":[{"given":"Lei","family":"Wang","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Feng","family":"Zou","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Xinhong","family":"Hei","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Dongdong","family":"Yang","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Debao","family":"Chen","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Qiaoyong","family":"Jiang","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Zijian","family":"Cao","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2014,6,10]]},"reference":[{"issue":"4300","key":"1627_CR1","doi-asserted-by":"crossref","first-page":"287","DOI":"10.1126\/science.267326","volume":"197","author":"MC Mackey","year":"1977","unstructured":"Mackey MC, Glass L (1977) Oscillation and chaos in physiological control systems. Science 197(4300):287\u2013289","journal-title":"Science"},{"issue":"5","key":"1627_CR2","doi-asserted-by":"crossref","first-page":"5083","DOI":"10.1103\/PhysRevE.56.5083","volume":"56","author":"MJ B\u00fcnner","year":"1997","unstructured":"B\u00fcnner MJ, Meyer T, Kittel A et al (1997) Recovery of the time-evolution equation of time-delay systems from time series. Phys Rev E 56(5):5083","journal-title":"Phys Rev E"},{"issue":"1","key":"1627_CR3","doi-asserted-by":"crossref","first-page":"11","DOI":"10.1007\/s00521-011-0741-0","volume":"22","author":"JP Donate","year":"2013","unstructured":"Donate JP, Li X, S\u00e1nchez GG, de Miguel AS (2013) Time series forecasting by evolving artificial neural networks with genetic algorithms, differential evolution and estimation of distribution algorithm. Neural Comput Appl 22(1):11\u201320","journal-title":"Neural Comput Appl"},{"issue":"2","key":"1627_CR4","doi-asserted-by":"crossref","first-page":"127","DOI":"10.1007\/s00521-007-0165-z","volume":"18","author":"MB Nasr","year":"2008","unstructured":"Nasr MB, Chtourou M (2008) A fuzzy neighborhood-based training algorithm for feedforward neural networks. Neural Comput Appl 18(2):127\u2013133","journal-title":"Neural Comput Appl"},{"issue":"2","key":"1627_CR5","doi-asserted-by":"crossref","first-page":"101","DOI":"10.1007\/s00521-004-0412-5","volume":"13","author":"JM G\u00f3rriz","year":"2004","unstructured":"G\u00f3rriz JM, Puntonet CG, Salmer\u00f3n M et al (2004) A new model for time-series forecasting using radial basis functions and exogenous data. Neural Comput Appl 13(2):101\u2013111","journal-title":"Neural Comput Appl"},{"issue":"4","key":"1627_CR6","doi-asserted-by":"crossref","first-page":"568","DOI":"10.1109\/5326.897083","volume":"30","author":"R Sitte","year":"2000","unstructured":"Sitte R, Sitte J (2000) Analysis of the predictive ability of time delay neural networks applied to the S&P 500 time series. IEEE Trans Syst Man Cybern Part C Appl Rev 30(4):568\u2013572","journal-title":"IEEE Trans Syst Man Cybern Part C Appl Rev"},{"issue":"10","key":"1627_CR7","doi-asserted-by":"crossref","first-page":"1527","DOI":"10.1109\/81.886983","volume":"47","author":"L Chen","year":"2000","unstructured":"Chen L, Chen G (2000) Fuzzy modeling, prediction, and control of uncertain chaotic systems based on time series. IEEE transactions on circuits and systems-I: Fundamental theory and applications 47(10):1527\u20131531","journal-title":"IEEE transactions on circuits and systems-I: Fundamental theory and applications"},{"issue":"9","key":"1627_CR8","doi-asserted-by":"crossref","first-page":"8474","DOI":"10.1016\/j.eswa.2012.01.171","volume":"39","author":"VA Gromov","year":"2012","unstructured":"Gromov VA, Shulga AN (2012) Chaotic time series prediction with employment of ant colony optimization[J]. Expert Syst Appl 39(9):8474\u20138478","journal-title":"Expert Syst Appl"},{"key":"1627_CR9","author":"M Sheikhan","year":"2012","unstructured":"Sheikhan M, Mohammadi N (2012) Time series prediction using PSO-optimized neural network and hybrid feature selection algorithm for IEEE load data. Neural Comput Appl. doi: 10.1007\/s00521-012-0980-8","journal-title":"Neural Comput Appl"},{"issue":"7","key":"1627_CR10","doi-asserted-by":"crossref","first-page":"8419","DOI":"10.1016\/j.eswa.2011.01.037","volume":"38","author":"J Wang","year":"2011","unstructured":"Wang J, Chi D, Wu J, Lu HY (2011) Chaotic time series method combined with particle swarm optimization and trend adjustment for electricity demand forecasting. Expert Syst Appl 38(7):8419\u20138429","journal-title":"Expert Syst Appl"},{"issue":"1","key":"1627_CR11","doi-asserted-by":"crossref","first-page":"243","DOI":"10.1007\/BF02532251","volume":"21","author":"H Akaike","year":"1969","unstructured":"Akaike H (1969) Fitting autoregressive models for prediction. Annals of the institute of Statistical Mathematics 21(1):243\u2013247","journal-title":"Annals of the institute of Statistical Mathematics"},{"issue":"1","key":"1627_CR12","doi-asserted-by":"crossref","first-page":"334","DOI":"10.1016\/j.amc.2007.09.067","volume":"199","author":"A Ben Mabrouk","year":"2008","unstructured":"Ben Mabrouk A, Ben Abdallah N, Dhifaoui Z (2008) Wavelet decomposition and autoregressive model for time series prediction. Appl Math Comput 199(1):334\u2013340","journal-title":"Appl Math Comput"},{"issue":"7","key":"1627_CR13","doi-asserted-by":"crossref","first-page":"3061","DOI":"10.1109\/TSP.2008.919396","volume":"56","author":"J Navarro-Moreno","year":"2008","unstructured":"Navarro-Moreno J (2008) ARMA prediction of widely linear systems by using the innovations algorithm. IEEE Trans Signal Process 56(7):3061\u20133068","journal-title":"IEEE Trans Signal Process"},{"key":"1627_CR14","doi-asserted-by":"crossref","DOI":"10.1007\/978-3-540-71918-2","volume-title":"Forecasting with exponential smoothing","author":"RJ Hyndman","year":"2008","unstructured":"Hyndman RJ (2008) Forecasting with exponential smoothing. Springer, New York"},{"issue":"5","key":"1627_CR15","doi-asserted-by":"crossref","first-page":"547","DOI":"10.1016\/j.autcon.2008.11.007","volume":"18","author":"Y Lu","year":"2009","unstructured":"Lu Y, AbouRizk SM (2009) Automated Box-Jenkins forecasting modelling. Automation in Construction 18(5):547\u2013558","journal-title":"Automation in Construction"},{"issue":"2","key":"1627_CR16","doi-asserted-by":"crossref","first-page":"1280","DOI":"10.1016\/j.eswa.2007.11.057","volume":"36","author":"M Han","year":"2009","unstructured":"Han M, Wang Y (2009) Analysis and modeling of multivariate chaotic time series based on neural network. Expert Syst Appl 36(2):1280\u20131290","journal-title":"Expert Syst Appl"},{"key":"1627_CR17","doi-asserted-by":"crossref","first-page":"12","DOI":"10.1016\/j.knosys.2013.01.030","volume":"46","author":"P Singh","year":"2013","unstructured":"Singh P, Borah B (2013) High-order fuzzy-neuro expert system for time series forecasting. Knowl-Based Syst 46:12\u201321","journal-title":"Knowl-Based Syst"},{"issue":"2","key":"1627_CR18","doi-asserted-by":"crossref","first-page":"24","DOI":"10.1109\/MCI.2009.932254","volume":"4","author":"N Sapankevych","year":"2009","unstructured":"Sapankevych N, Sankar R (2009) Time series prediction using support vector machines: a survey. IEEE Comput Intell Mag 4(2):24\u201338","journal-title":"IEEE Comput Intell Mag"},{"issue":"4","key":"1627_CR19","doi-asserted-by":"crossref","first-page":"4312","DOI":"10.1016\/j.eswa.2010.09.100","volume":"38","author":"YK Bang","year":"2011","unstructured":"Bang YK, Lee CK (2011) Fuzzy time series prediction using hierarchical clustering algorithms. Expert Syst Appl 38(4):4312\u20134325","journal-title":"Expert Syst Appl"},{"key":"1627_CR20","first-page":"2938","volume":"2006","author":"H Dhahri","year":"2006","unstructured":"Dhahri H, Alimi AM (2006) The modified differential evolution and the RBF (MDE-RBF) neural network for time series prediction. Neural Networks, 2006. IJCNN\u201906. International Joint Conference on. IEEE 2006:2938\u20132943","journal-title":"International Joint Conference on. IEEE"},{"issue":"5","key":"1627_CR21","doi-asserted-by":"crossref","first-page":"2681","DOI":"10.1016\/j.chaos.2008.09.057","volume":"41","author":"H Mirzaee","year":"2009","unstructured":"Mirzaee H (2009) Linear combination rule in genetic algorithm for optimization of finite impulse response neural network to predict natural chaotic time series. Chaos, Solitons Fractals 41(5):2681\u20132689","journal-title":"Chaos, Solitons Fractals"},{"issue":"5","key":"1627_CR22","doi-asserted-by":"crossref","first-page":"3132","DOI":"10.1016\/j.chaos.2009.04.045","volume":"42","author":"Y Tang","year":"2009","unstructured":"Tang Y, Guan X (2009) Parameter estimation of chaotic system with time-delay: a differential evolution approach. Chaos, Solitons Fractals 42(5):3132\u20133139","journal-title":"Chaos, Solitons Fractals"},{"issue":"2","key":"1627_CR23","doi-asserted-by":"crossref","first-page":"2805","DOI":"10.1016\/j.eswa.2008.01.061","volume":"36","author":"L Zhao","year":"2009","unstructured":"Zhao L, Yang Y (2009) PSO-based single multiplicative neuron model for time series prediction. Expert Syst Appl 36(2):2805\u20132812","journal-title":"Expert Syst Appl"},{"issue":"9","key":"1627_CR24","doi-asserted-by":"crossref","first-page":"11406","DOI":"10.1016\/j.eswa.2011.03.013","volume":"38","author":"B Samanta","year":"2011","unstructured":"Samanta B (2011) Prediction of chaotic time series using computational intelligence. Expert Syst Appl 38(9):11406\u201311411","journal-title":"Expert Syst Appl"},{"key":"1627_CR25","doi-asserted-by":"crossref","first-page":"036203","DOI":"10.1103\/PhysRevE.83.036203","volume":"83","author":"C Dai","year":"2011","unstructured":"Dai C, Chen W, Li L, Zhu Y, Yang Y (2011) Seeker optimization algorithm for parameter estimation of time-delay chaotic systems. Phys Rev E 83:036203","journal-title":"Phys Rev E"},{"issue":"9","key":"1627_CR26","doi-asserted-by":"crossref","first-page":"8474","DOI":"10.1016\/j.eswa.2012.01.171","volume":"39","author":"VA Gromov","year":"2012","unstructured":"Gromov VA, Shulga AN (2012) Chaotic time series prediction with employment of ant colony optimization. Expert Syst Appl 39(9):8474\u20138478","journal-title":"Expert Syst Appl"},{"issue":"3","key":"1627_CR27","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. Computer-Aided Design 43(3):303\u2013315","journal-title":"Computer-Aided Design"},{"issue":"1","key":"1627_CR28","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1016\/j.ins.2011.08.006","volume":"183","author":"RV Rao","year":"2012","unstructured":"Rao RV, Savsani VJ, Vakharia DP (2012) Teaching-learning-based optimization: an optimization method for continuous non-linear large scale problems. Inf Sci 183(1):1\u201315","journal-title":"Inf Sci"},{"issue":"8","key":"1627_CR29","doi-asserted-by":"crossref","first-page":"1577","DOI":"10.1016\/j.engappai.2012.07.004","volume":"25","author":"T Niknam","year":"2012","unstructured":"Niknam T, Azizipanah-Abarghooee R, Rasoul Narimani M (2012) A new multi objective optimization approach based on TLBO for location of automatic voltage regulators in distribution systems. Eng Appl Artif Intell 25(8):1577\u20131588","journal-title":"Eng Appl Artif Intell"},{"issue":"1","key":"1627_CR30","doi-asserted-by":"crossref","first-page":"524","DOI":"10.1016\/j.engappai.2012.06.007","volume":"26","author":"RV Rao","year":"2013","unstructured":"Rao RV, Kalyankar VD (2013) Parameter optimization of modern machining processes using teaching-learning-based optimization algorithm. Eng Appl Artif Intell 26(1):524\u2013531","journal-title":"Eng Appl Artif Intell"},{"key":"1627_CR31","doi-asserted-by":"crossref","first-page":"11","DOI":"10.1016\/j.chemolab.2013.04.012","volume":"126","author":"G Li","year":"2013","unstructured":"Li G, Niu P, Zhang W, Liu Y (2013) Model NOx emissions by least squares support vector machine with tuning based on ameliorated teaching-learning-based optimization. Chemometrics and Intelligent Laboratory Systems 126:11\u201320","journal-title":"Chemometrics and Intelligent Laboratory Systems"},{"issue":"3","key":"1627_CR32","first-page":"710","volume":"20","author":"RV Rao","year":"2013","unstructured":"Rao RV, Patel V (2013) An improved teaching-learning-based optimization algorithm for solving unconstrained optimization problems. Scientia Iranica 20(3):710\u2013720","journal-title":"Scientia Iranica"},{"issue":"4","key":"1627_CR33","first-page":"535","volume":"3","author":"RV Rao","year":"2012","unstructured":"Rao RV, Patel V (2012) An elitist teaching-learning-based optimization algorithm for solving complex constrained optimization problems. Int J Ind Eng Comput 3(4):535\u2013560","journal-title":"Int J Ind Eng Comput"},{"issue":"1","key":"1627_CR34","first-page":"29","volume":"4","author":"RV Rao","year":"2013","unstructured":"Rao RV, Patel V (2013) Comparative performance of an elitist teaching-learning-based optimization algorithm for solving unconstrained optimization problems. Int J Ind Eng Comput 4(1):29\u201350","journal-title":"Int J Ind Eng Comput"},{"key":"1627_CR35","doi-asserted-by":"crossref","first-page":"177","DOI":"10.1016\/j.compstruc.2012.12.011","volume":"119","author":"SO Degertekin","year":"2013","unstructured":"Degertekin SO, Hayalioglu MS (2013) Sizing truss structures using teaching-learning-based optimization. Comput Struct 119:177\u2013188","journal-title":"Comput Struct"},{"key":"1627_CR36","doi-asserted-by":"crossref","first-page":"65","DOI":"10.1016\/j.ijepes.2013.02.023","volume":"50","author":"JA Mart\u00edn Garc\u00eda","year":"2013","unstructured":"Mart\u00edn Garc\u00eda JA, Gil Mena AJ (2013) Optimal distributed generation location and size using a modified teaching-learning based optimization algorithm. Int J Electr Power Energy Syst 50:65\u201375","journal-title":"Int J Electr Power Energy Syst"},{"key":"1627_CR37","doi-asserted-by":"crossref","first-page":"341","DOI":"10.1023\/A:1008202821328","volume":"11","author":"R Storn","year":"1997","unstructured":"Storn R, Price K (1997) Differential evolution\u2014A simple and efficient heuristic for global optimization over continuous spaces. J Global Optim 11:341\u2013359","journal-title":"J Global Optim"},{"issue":"6","key":"1627_CR38","doi-asserted-by":"crossref","first-page":"646","DOI":"10.1109\/TEVC.2006.872133","volume":"10","author":"J Brest","year":"2006","unstructured":"Brest J, Greiner S, Boskovic B, Mernik M, Zumer V (2006) Self-adapting control parameters in differential evolution: a comparative study on numerical benchmark problems. IEEE Trans Evol Comput 10(6):646\u2013657","journal-title":"IEEE Trans Evol Comput"},{"issue":"2","key":"1627_CR39","doi-asserted-by":"crossref","first-page":"398","DOI":"10.1109\/TEVC.2008.927706","volume":"13","author":"AK Qin","year":"2009","unstructured":"Qin AK, Huang VL, Suganthan PN (2009) Differential evolution algorithm with strategy adaptation for global numerical optimization. IEEE Trans Evol Comput 13(2):398\u2013417","journal-title":"IEEE Trans Evol Comput"},{"issue":"1","key":"1627_CR40","doi-asserted-by":"crossref","first-page":"58","DOI":"10.1109\/4235.985692","volume":"6","author":"M Clerc","year":"2002","unstructured":"Clerc M, Kennedy J (2002) 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"},{"issue":"3","key":"1627_CR41","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 IEEE Transactions on Evolutionary Computation 8(3):204\u2013210","journal-title":"IEEE IEEE Transactions on Evolutionary Computation"},{"key":"1627_CR42","unstructured":"K. E. Parsopoulos and M. N. Vrahatis (2004). UPSO\u2014A unified particle swarm optimization scheme. In Lecture Series on Computational Sciences, 868\u2013873"}],"container-title":["Neural Computing and Applications"],"original-title":[],"language":"en","link":[{"URL":"http:\/\/link.springer.com\/content\/pdf\/10.1007\/s00521-014-1627-8.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"http:\/\/link.springer.com\/article\/10.1007\/s00521-014-1627-8\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"http:\/\/link.springer.com\/content\/pdf\/10.1007\/s00521-014-1627-8","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2019,8,11]],"date-time":"2019-08-11T11:40:14Z","timestamp":1565523614000},"score":1,"resource":{"primary":{"URL":"http:\/\/link.springer.com\/10.1007\/s00521-014-1627-8"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2014,6,10]]},"references-count":42,"journal-issue":{"issue":"6","published-print":{"date-parts":[[2014,11]]}},"alternative-id":["1627"],"URL":"https:\/\/doi.org\/10.1007\/s00521-014-1627-8","relation":{},"ISSN":["0941-0643","1433-3058"],"issn-type":[{"value":"0941-0643","type":"print"},{"value":"1433-3058","type":"electronic"}],"subject":[],"published":{"date-parts":[[2014,6,10]]}}}