{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,26]],"date-time":"2026-03-26T16:05:31Z","timestamp":1774541131311,"version":"3.50.1"},"reference-count":35,"publisher":"Springer Science and Business Media LLC","issue":"3-4","license":[{"start":{"date-parts":[[2011,12,8]],"date-time":"2011-12-08T00:00:00Z","timestamp":1323302400000},"content-version":"tdm","delay-in-days":0,"URL":"http:\/\/www.springer.com\/tdm"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Neural Comput & Applic"],"published-print":{"date-parts":[[2013,3]]},"DOI":"10.1007\/s00521-011-0771-7","type":"journal-article","created":{"date-parts":[[2011,12,7]],"date-time":"2011-12-07T04:09:32Z","timestamp":1323230972000},"page":"803-810","source":"Crossref","is-referenced-by-count":59,"title":["An enhanced extreme learning machine based on ridge regression for regression"],"prefix":"10.1007","volume":"22","author":[{"given":"Guoqiang","family":"Li","sequence":"first","affiliation":[]},{"given":"Peifeng","family":"Niu","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2011,12,8]]},"reference":[{"key":"771_CR1","doi-asserted-by":"crossref","unstructured":"Han F, Ling Q-H, Huang D-S (2010) An improved approximation approach incorporating particle swarm optimization and a priori information into neural networks. Neural Comput Appl 19:255\u2013261","DOI":"10.1007\/s00521-009-0274-y"},{"key":"771_CR2","doi-asserted-by":"crossref","unstructured":"Han F, Huang D-S (2008) A new constrained learning algorithm for function approximation by encoding a priori information into feedforward neural networks. Neural Comput Appl 17:433\u2013439","DOI":"10.1007\/s00521-007-0135-5"},{"key":"771_CR3","doi-asserted-by":"crossref","unstructured":"Liang NY, Huang GB, Saratchandran P, Sundararajan N (2006) A fast and accurate online sequential learning algorithm for feedforward networks. IEEE Trans Neural Netw 17:1411\u20131423","DOI":"10.1109\/TNN.2006.880583"},{"key":"771_CR4","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 38:11406\u201311411","journal-title":"Expert Syst Appl"},{"key":"771_CR5","doi-asserted-by":"crossref","unstructured":"Tsai H-C, Lin Y-H (2011) Modular neural network programming with genetic optimization. Expert Syst Appl 38:11032\u201311039","DOI":"10.1016\/j.eswa.2011.02.147"},{"key":"771_CR6","doi-asserted-by":"crossref","unstructured":"Balamurugan G, Aravindhababu P (2011) ANN based online voltage estimation. Appl Soft Comput. doi: 10.1016\/j.asoc.2011.08.041","DOI":"10.1016\/j.asoc.2011.08.041"},{"key":"771_CR7","doi-asserted-by":"crossref","unstructured":"Huang G-B, Zhu Q-Y, Siew C-K (2006) Extreme learning machine: theory and applications. Neurocomputing 70:489\u2013501","DOI":"10.1016\/j.neucom.2005.12.126"},{"key":"771_CR8","doi-asserted-by":"crossref","unstructured":"Suresh S, Sarawathi S, Sundararajan N (2010) Performance enhancement of extreme learning for multi-category sparse data classification problems. Eng Appl Artif Intell 23:1149\u20131157","DOI":"10.1016\/j.engappai.2010.06.009"},{"key":"771_CR9","doi-asserted-by":"crossref","unstructured":"Minhas R, Mohammed AA, Jonathan M, Wu Q (2010) A fast recognition framework based on extreme learning machine using hybrid object information. Neurocomputing 73:1831\u20131839","DOI":"10.1016\/j.neucom.2009.11.049"},{"key":"771_CR10","doi-asserted-by":"crossref","unstructured":"Pan C, Park D, Yang Y, Yoo H (2011) Leukocyte image segmentation by visual attention and extreme learning machine. Neural Comput Appl. doi: 10.1007\/s00521-011-0522-9","DOI":"10.1007\/s00521-011-0522-9"},{"key":"771_CR11","doi-asserted-by":"crossref","unstructured":"Hu X-f, Zhao Z, Wang S, Wang F-l, He D-k, Wu S-k (2008) Multi-stage extreme learning machine for fault diagnosis on hydraulic tube tester. Neural Comput Appl 17:399\u2013403","DOI":"10.1007\/s00521-007-0139-1"},{"key":"771_CR12","doi-asserted-by":"crossref","unstructured":"Zhang RX, Huang GB, Sundararajan N, Saratchandran P (2007) Multicategory classification using an extreme learning machine for microarray gene expression cancer diagnosis. IEEE ACM Trans Comput Biol Bioinform 4(3):485\u2013495","DOI":"10.1109\/tcbb.2007.1012"},{"key":"771_CR13","doi-asserted-by":"crossref","unstructured":"Huang G-B, Chen L, Siew C-K (2006) Universal approximation using incremental constructive feedforward networks with random hidden nodes. IEEE Trans Neural Netw 17(4):879\u2013892","DOI":"10.1109\/TNN.2006.875977"},{"key":"771_CR14","doi-asserted-by":"crossref","unstructured":"Nizar AH, Dong ZY, Wang Y (2008) Power utility nontechnical loss analysis with extreme learning machine method. IEEE Trans Power Syst 23(3):946\u2013955","DOI":"10.1109\/TPWRS.2008.926431"},{"key":"771_CR15","doi-asserted-by":"crossref","unstructured":"Yeu CWT, Lim MH, Huang GB, Agarwal A, Ong YS (2006) A new machine learning paradigm for terrain reconstruction. IEEE Geosci Remote Sens Lett 3(3):382\u2013386","DOI":"10.1109\/LGRS.2006.873687"},{"issue":"1\u20133","key":"771_CR16","doi-asserted-by":"crossref","first-page":"262","DOI":"10.1016\/j.neucom.2008.01.016","volume":"72","author":"G Wang","year":"2008","unstructured":"Wang G, Zhao Y, Wang D (2008) A protein secondary structure prediction framework based on the Extreme Learning Machine. Neurocomputing 72(1\u20133):262\u2013268","journal-title":"Neurocomputing"},{"key":"771_CR17","doi-asserted-by":"crossref","unstructured":"Tang X, Han M (2009) Partial Lanczos extreme learning machine for single-output regression problems. Neurocomputing 72:3066\u20133076","DOI":"10.1016\/j.neucom.2009.03.016"},{"key":"771_CR18","doi-asserted-by":"crossref","unstructured":"Feng G, Huang G-B, Lin Q, Gay R (2009) Error minimized extreme learning machine with growth of hidden nodes and incremental learning. IEEE Trans Neural Netw 20(8):1352\u20131357","DOI":"10.1109\/TNN.2009.2024147"},{"key":"771_CR19","doi-asserted-by":"crossref","first-page":"3391","DOI":"10.1016\/j.neucom.2009.02.013","volume":"72","author":"Y Lan","year":"2009","unstructured":"Lan Y, Soh YC, Huang G-B (2009) Ensemble of online sequential extreme learning machine. Neurocomputing 72:3391\u20133395","journal-title":"Neurocomputing"},{"key":"771_CR20","doi-asserted-by":"crossref","unstructured":"Li G, Liu M, Dong M (2010) A new online learning algorithm for structure-adjustable extreme learning machine. Comput Math Appl 60:377\u2013389","DOI":"10.1016\/j.camwa.2010.03.023"},{"key":"771_CR21","doi-asserted-by":"crossref","first-page":"359","DOI":"10.1016\/j.neucom.2008.01.005","volume":"72","author":"H-J Rong","year":"2008","unstructured":"Rong H-J, Ong Y-S, Tan A-H, Zhu Z-X (2008) A fast pruned-extreme learning machine for classification problem. Neurocomputing 72:359\u2013366","journal-title":"Neurocomputing"},{"issue":"10","key":"771_CR22","doi-asserted-by":"crossref","first-page":"1759","DOI":"10.1016\/j.patcog.2005.03.028","volume":"38","author":"QY Zhu","year":"2005","unstructured":"Zhu QY, Qin AK, Suganthan PN, Huang GB (2005) Evolutionary extreme learning machine. Pattern Recogn 38(10):1759\u20131763","journal-title":"Pattern Recogn"},{"issue":"16\u201318","key":"771_CR23","doi-asserted-by":"crossref","first-page":"3460","DOI":"10.1016\/j.neucom.2007.10.008","volume":"71","author":"G-B Huang","year":"2008","unstructured":"Huang G-B, Chen L (2008) Enhanced random search based incremental extreme learning machine. Neurocomputing 71(16\u201318):3460\u20133468","journal-title":"Neurocomputing"},{"issue":"16\u201318","key":"771_CR24","doi-asserted-by":"crossref","first-page":"3056","DOI":"10.1016\/j.neucom.2007.02.009","volume":"70","author":"GB Huang","year":"2007","unstructured":"Huang GB, Chen L (2007) Convex incremental extreme learning machine. Neurocomputing 70(16\u201318):3056\u20133062","journal-title":"Neurocomputing"},{"issue":"16\u201318","key":"771_CR25","doi-asserted-by":"crossref","first-page":"2369","DOI":"10.1016\/j.neucom.2006.02.013","volume":"69","author":"F Han","year":"2006","unstructured":"Han F, Huang DS (2006) Improved extreme learning machine for function approximation by encoding a priori information. Neurocomputing 69(16\u201318):2369\u20132373","journal-title":"Neurocomputing"},{"key":"771_CR26","doi-asserted-by":"crossref","unstructured":"Hawkinsa DM, Yin X (2002) A faster algorithm for ridge regression of reduced rank data. Comput Stat Data Anal 40:253\u2013262","DOI":"10.1016\/S0167-9473(02)00034-8"},{"key":"771_CR27","doi-asserted-by":"crossref","unstructured":"Foucart T (1999) Stability of the inverse correlation matrix. Partial ridge regression. J Stat Plan Inference 77:141\u2013154","DOI":"10.1016\/S0378-3758(98)00195-5"},{"key":"771_CR28","doi-asserted-by":"crossref","unstructured":"Turlach BA (2006) An even faster algorithm for ridge regression of reduced rank data. Comput Stat Data Anal 50:642\u2013658","DOI":"10.1016\/j.csda.2004.09.007"},{"key":"771_CR29","doi-asserted-by":"crossref","unstructured":"Tutz G, Binder H (2007) Boosting ridge regression. Comput Stat Data Anal 51:6044\u20136059","DOI":"10.1016\/j.csda.2006.11.041"},{"key":"771_CR30","doi-asserted-by":"crossref","unstructured":"Lawless JF, Wang P (1976) A simulation study of ridge and other regression estimators. Commun Stat Theory Methods A5:307\u2013323","DOI":"10.1080\/03610927608827353"},{"key":"771_CR31","doi-asserted-by":"crossref","unstructured":"Lipovetsky S (2010) Enhanced ridge regressions. Math Comput Model 51:338\u2013348","DOI":"10.1016\/j.mcm.2009.12.028"},{"key":"771_CR32","doi-asserted-by":"crossref","unstructured":"Wan ATK (2002) On generalized ridge regression estimators under collinearity and balanced loss. Appl Math Comput 129:455\u2013467","DOI":"10.1016\/S0096-3003(01)00056-X"},{"key":"771_CR33","doi-asserted-by":"crossref","unstructured":"Akdeniz F, Yuksel G, Wan ATK (2004) The moments of the operational almost unbiased ridge regression estimator. Appl Math Comput 153:673\u2013684","DOI":"10.1016\/S0096-3003(03)00663-5"},{"key":"771_CR34","first-page":"1","volume":"70","author":"Y Lan","year":"2010","unstructured":"Lan Y, Soh Y-C, Huang G-B (2010) Constructive hidden nodes selection of extreme learning machine. Neurocomputing 70:1\u20139","journal-title":"Neurocomputing"},{"key":"771_CR35","doi-asserted-by":"crossref","unstructured":"Li G, Niu P, Xiao X (2011) Development and investigation of efficient artificial bee colony algorithm for numerical function optimization. Appl Soft Comput. doi: 10.1016\/j.asoc.2011.08.040","DOI":"10.1016\/j.asoc.2011.08.040"}],"container-title":["Neural Computing and Applications"],"original-title":[],"language":"en","link":[{"URL":"http:\/\/link.springer.com\/content\/pdf\/10.1007\/s00521-011-0771-7.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"http:\/\/link.springer.com\/article\/10.1007\/s00521-011-0771-7\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"http:\/\/link.springer.com\/content\/pdf\/10.1007\/s00521-011-0771-7","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2019,5,29]],"date-time":"2019-05-29T02:14:37Z","timestamp":1559096077000},"score":1,"resource":{"primary":{"URL":"http:\/\/link.springer.com\/10.1007\/s00521-011-0771-7"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2011,12,8]]},"references-count":35,"journal-issue":{"issue":"3-4","published-print":{"date-parts":[[2013,3]]}},"alternative-id":["771"],"URL":"https:\/\/doi.org\/10.1007\/s00521-011-0771-7","relation":{},"ISSN":["0941-0643","1433-3058"],"issn-type":[{"value":"0941-0643","type":"print"},{"value":"1433-3058","type":"electronic"}],"subject":[],"published":{"date-parts":[[2011,12,8]]}}}