{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,10,30]],"date-time":"2025-10-30T22:25:41Z","timestamp":1761863141469},"reference-count":24,"publisher":"Springer Science and Business Media LLC","issue":"S1","license":[{"start":{"date-parts":[[2012,7,10]],"date-time":"2012-07-10T00:00:00Z","timestamp":1341878400000},"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":[[2013,5]]},"DOI":"10.1007\/s00521-012-1044-9","type":"journal-article","created":{"date-parts":[[2012,7,9]],"date-time":"2012-07-09T07:34:47Z","timestamp":1341819287000},"page":"75-82","source":"Crossref","is-referenced-by-count":7,"title":["Structure and weight optimization of neural network based on CPA-MLR and its application in naphtha dry point soft sensor"],"prefix":"10.1007","volume":"22","author":[{"given":"Yang","family":"Wang","sequence":"first","affiliation":[]},{"given":"Chao","family":"Chen","sequence":"additional","affiliation":[]},{"given":"Xuefeng","family":"Yan","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2012,7,10]]},"reference":[{"key":"1044_CR1","doi-asserted-by":"crossref","first-page":"152","DOI":"10.1016\/j.chemolab.2010.07.002","volume":"103","author":"Y Xuefeng","year":"2010","unstructured":"Xuefeng Y (2010) Hybrid artificial neural network based on BP-PLSR and its application in development of soft sensors. Chemom Intell Lab Syst 103:152\u2013159","journal-title":"Chemom Intell Lab Syst"},{"key":"1044_CR2","doi-asserted-by":"crossref","first-page":"230","DOI":"10.1016\/S1003-9953(06)60031-5","volume":"15","author":"L Wang","year":"2006","unstructured":"Wang L, Shao C, Wang H, Hong W (2006) Radial basis function neural networks-based modeling of the membrane separation process: hydrogen recovery from refinery gases. J Nat Gas Chem 15:230\u2013234","journal-title":"J Nat Gas Chem"},{"key":"1044_CR3","first-page":"1642","volume":"3","author":"MT Hagan","year":"1999","unstructured":"Hagan MT, Demuth HB (1999) Neural networks for control. Am Cont Conf Proc 3:1642\u20131656","journal-title":"Am Cont Conf Proc"},{"key":"1044_CR4","doi-asserted-by":"crossref","first-page":"985","DOI":"10.1016\/j.snb.2007.09.030","volume":"129","author":"A Jim\u00e9nez","year":"2008","unstructured":"Jim\u00e9nez A, Beltr\u00e1n G, Aguilera MP, Uceda M (2008) A sensor-software based on artificial neural network for the optimization of olive oil elaboration process. Sens Actuators, B 129:985\u2013990","journal-title":"Sens Actuators, B"},{"key":"1044_CR5","doi-asserted-by":"crossref","first-page":"293","DOI":"10.1016\/S0952-1976(97)00055-9","volume":"11","author":"HB Su","year":"1998","unstructured":"Su HB, Fan LT, Schlup JR (1998) Monitoring the process of curing of epoxy\/graphite fiber composites with a recurrent neural network as a soft sensor. Eng Appl Artif Intel 11:293\u2013306","journal-title":"Eng Appl Artif Intel"},{"key":"1044_CR6","doi-asserted-by":"crossref","first-page":"707","DOI":"10.1016\/S0893-6080(99)00018-0","volume":"12","author":"M Lehtokangas","year":"1999","unstructured":"Lehtokangas M (1999) Modeling with constructive back propagation. Neural Netw 12:707\u2013716","journal-title":"Neural Netw"},{"key":"1044_CR7","doi-asserted-by":"crossref","first-page":"100","DOI":"10.1016\/j.asoc.2004.12.005","volume":"6","author":"MH Nguye","year":"2005","unstructured":"Nguye MH, Hussein AA, Robert IM (2005) Stopping criteria for ensemble of evolutionary artificial neural networks. Appl Soft Comput 6:100\u2013107","journal-title":"Appl Soft Comput"},{"key":"1044_CR8","doi-asserted-by":"crossref","first-page":"886","DOI":"10.1016\/j.ics.2004.03.238","volume":"1268","author":"RM Zur","year":"2004","unstructured":"Zur RM, Jiang Y, Metz CE (2004) Comparison of two methods of adding jitter to artificial neural network training. Int Congr Ser 1268:886\u2013889","journal-title":"Int Congr Ser"},{"key":"1044_CR9","first-page":"598","volume-title":"Advances in neural information processing systems 2","author":"Y Cun Le","year":"1990","unstructured":"Le Cun Y, Denker JS, Solla SA (1990) Optimal brain damage. In: Touretzky DS (ed) Advances in neural information processing systems 2. Morgan Kaufmann, San Mateo, pp 598\u2013605"},{"key":"1044_CR10","first-page":"101","volume":"14","author":"L Xiqun","year":"1997","unstructured":"Xiqun L, Yinglin Y (1997) A method of dynamic pruning the hidden layer nodes in a feedforward neural network. Chin J Control Theory J Control Theory (China) 14:101\u2013104","journal-title":"Chin J Control Theory J Control Theory (China)"},{"key":"1044_CR11","doi-asserted-by":"crossref","first-page":"3553","DOI":"10.1016\/j.neucom.2007.08.028","volume":"71","author":"A Luchetta","year":"2008","unstructured":"Luchetta A (2008) Automatic generation of the optimum threshold for parameter weighted pruning in multiple heterogeneous output neural networks. Neurocomputing 71:3553\u20133560","journal-title":"Neurocomputing"},{"key":"1044_CR12","volume-title":"Multilayer perceptron structured initialization and separating mean processing","author":"WH Delashmit","year":"2003","unstructured":"Delashmit WH (2003) Multilayer perceptron structured initialization and separating mean processing. University of Texas, Dissertation"},{"key":"1044_CR13","doi-asserted-by":"crossref","first-page":"660","DOI":"10.1016\/j.engappai.2008.11.002","volume":"22","author":"C MacLeod","year":"2009","unstructured":"MacLeod C, Maxwell G, Muthuraman S (2009) Incremental growth in modular neural networks. Eng Appl Artif Intel 22:660\u2013666","journal-title":"Eng Appl Artif Intel"},{"key":"1044_CR14","unstructured":"Qian L, Yongxian W, Youqin Z (2005) Hybrid pruning algorithm for artificial network training, Chin J Tsinghua Uni Sci Tech Tsinghua University (Science and Technology) (China) 45:831\u2013834"},{"key":"1044_CR15","doi-asserted-by":"crossref","first-page":"56","DOI":"10.1016\/j.chemolab.2010.10.010","volume":"105","author":"D Ballabio","year":"2011","unstructured":"Ballabio D, Vasighi M, Consonni V, Kompany-Zareh M (2011) Genetic algorithms for architecture optimisation of counter-propagation artificial neural networks. Chemometr Intell Lab 105:56\u201364","journal-title":"Chemometr Intell Lab"},{"key":"1044_CR16","first-page":"313","volume":"15","author":"HE Shudong","year":"1998","unstructured":"Shudong HE, Tan QU, Xiangqing H, Xinhan H (1998) Survey of architecture for multilayer feedforward neural networks. Contr Theor Appl Control Theory Appl 15:313\u2013319","journal-title":"Contr Theor Appl Control Theory Appl"},{"key":"1044_CR17","doi-asserted-by":"crossref","first-page":"544","DOI":"10.1016\/j.neucom.2005.11.005","volume":"70","author":"X Jinhua","year":"2006","unstructured":"Jinhua X, Ho DWC (2006) A new training and pruning algorithm based on node dependence and jacobian rank deficiency. Neurocomputing 70:544\u2013558","journal-title":"Neurocomputing"},{"key":"1044_CR18","doi-asserted-by":"crossref","first-page":"825","DOI":"10.1016\/j.neucom.2005.04.010","volume":"69","author":"X Zeng","year":"2006","unstructured":"Zeng X, Yeung DS (2006) Hidden neuron pruning of multilayer perceptrons using a quantified sensitivity measure. Neurocomputing 69:825\u2013837","journal-title":"Neurocomputing"},{"key":"1044_CR19","doi-asserted-by":"crossref","first-page":"505","DOI":"10.1016\/S0893-6080(96)00086-X","volume":"10","author":"C Schittenkopf","year":"1997","unstructured":"Schittenkopf C, Deco G, Brauer W (1997) Two strategies to avoid overfitting in feedforward networks. Neural Netw 10:505\u2013516","journal-title":"Neural Netw"},{"key":"1044_CR20","doi-asserted-by":"crossref","first-page":"183","DOI":"10.1016\/0893-6080(89)90003-8","volume":"2","author":"K-L Funahashi","year":"1989","unstructured":"Funahashi K-L (1989) On the approximate realization of continuous mapping by neural networks. Neural Netw 2:183\u2013192","journal-title":"Neural Netw"},{"key":"1044_CR21","doi-asserted-by":"crossref","first-page":"359","DOI":"10.1016\/0893-6080(89)90020-8","volume":"2","author":"K Hornik","year":"1989","unstructured":"Hornik K, Stinchcombe M, White H (1989) Multilayer feedforward networks are universal approximators. Neural Netw 2:359\u2013366","journal-title":"Neural Netw"},{"key":"1044_CR22","doi-asserted-by":"crossref","first-page":"551","DOI":"10.1016\/0893-6080(90)90005-6","volume":"3","author":"K Hornik","year":"1990","unstructured":"Hornik K, Stinchcombe M, White H (1990) Universal approximation of an unknown mapping and its derivatives using multilayer feedforward networks. Neural Netw 3:551\u2013560","journal-title":"Neural Netw"},{"key":"1044_CR23","first-page":"1511","volume":"56","author":"X Yan","year":"2005","unstructured":"Yan X (2005) Development of naphtha dry point soft sensor by adaptive partial least square regression. Chin J Chem Eng (China) 56:1511\u20131515","journal-title":"Chin J Chem Eng (China)"},{"key":"1044_CR24","doi-asserted-by":"crossref","first-page":"79","DOI":"10.1016\/S0893-6080(98)00105-1","volume":"12","author":"G Zhou","year":"1999","unstructured":"Zhou G, Si J (1999) Subset-based training and pruning of sgmoid neural network. Neural Netw 12:79\u201389","journal-title":"Neural Netw"}],"container-title":["Neural Computing and Applications"],"original-title":[],"language":"en","link":[{"URL":"http:\/\/link.springer.com\/content\/pdf\/10.1007\/s00521-012-1044-9.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"http:\/\/link.springer.com\/article\/10.1007\/s00521-012-1044-9\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"http:\/\/link.springer.com\/content\/pdf\/10.1007\/s00521-012-1044-9","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2019,5,28]],"date-time":"2019-05-28T22:14:43Z","timestamp":1559081683000},"score":1,"resource":{"primary":{"URL":"http:\/\/link.springer.com\/10.1007\/s00521-012-1044-9"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2012,7,10]]},"references-count":24,"journal-issue":{"issue":"S1","published-print":{"date-parts":[[2013,5]]}},"alternative-id":["1044"],"URL":"https:\/\/doi.org\/10.1007\/s00521-012-1044-9","relation":{},"ISSN":["0941-0643","1433-3058"],"issn-type":[{"value":"0941-0643","type":"print"},{"value":"1433-3058","type":"electronic"}],"subject":[],"published":{"date-parts":[[2012,7,10]]}}}