{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,22]],"date-time":"2026-04-22T13:18:30Z","timestamp":1776863910112,"version":"3.51.2"},"reference-count":55,"publisher":"Springer Science and Business Media LLC","issue":"3-4","license":[{"start":{"date-parts":[[2014,3,23]],"date-time":"2014-03-23T00:00:00Z","timestamp":1395532800000},"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":[[2014,9]]},"DOI":"10.1007\/s00521-014-1573-5","type":"journal-article","created":{"date-parts":[[2014,3,22]],"date-time":"2014-03-22T14:43:09Z","timestamp":1395499389000},"page":"859-869","source":"Crossref","is-referenced-by-count":95,"title":["Extracting the contribution of independent variables in neural network models: a new approach to handle instability"],"prefix":"10.1007","volume":"25","author":[{"given":"Juan","family":"de O\u00f1a","sequence":"first","affiliation":[]},{"given":"Concepci\u00f3n","family":"Garrido","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2014,3,23]]},"reference":[{"issue":"19","key":"1573_CR1","first-page":"2837","volume":"5","author":"D Akin","year":"2010","unstructured":"Akin D, Akba\u00e7 B (2010) A neural network (NN) model to predict intersection crashes based upon driver, vehicle and roadway surface characteristics. Sci Res Essays 5(19):2837\u20132847","journal-title":"Sci Res Essays"},{"key":"1573_CR2","doi-asserted-by":"crossref","first-page":"361","DOI":"10.1016\/j.jlp.2011.01.015","volume":"24","author":"A Azadeh","year":"2011","unstructured":"Azadeh A, Rouzbahman M, Saberi M, Fam IM (2011) An adaptative neural network algorithm for assessment and improvement of job satisfaction with respect to HSE and ergonomics program: the case of a gas refinery. J Loss Prev Process Ind 24:361\u2013370","journal-title":"J Loss Prev Process Ind"},{"key":"1573_CR3","unstructured":"Beale MH, Hagan MT, Demuth HB (2007) Neural Network Toolbox 7. User\u2019s Guide. MathWorks, Inc. 3 Apple Hill Drive Natic, MA 01760-2098"},{"key":"1573_CR4","doi-asserted-by":"crossref","first-page":"509","DOI":"10.1007\/s00521-007-0143-5","volume":"17","author":"M Cao","year":"2008","unstructured":"Cao M, Qiao P (2008) Neural network committee-based sensitivity analysis strategy for geotechnical engineering problems. Neural Comput Appl 17:509\u2013519","journal-title":"Neural Comput Appl"},{"key":"1573_CR5","doi-asserted-by":"crossref","unstructured":"Cortez P, Embrechts MJ (2011) Opening black box data mining models using sensitivity analysis. IEEE symposium series in computational intelligence, Paris, France, 4, 2011","DOI":"10.1109\/CIDM.2011.5949423"},{"key":"1573_CR6","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1016\/j.ins.2012.10.039","volume":"225","author":"P Cortez","year":"2013","unstructured":"Cortez P, Embrechts MJ (2013) Using sensitivity analysis and visualization techniques to open black box data mining models. Inf Sci 225:1\u201317","journal-title":"Inf Sci"},{"key":"1573_CR7","doi-asserted-by":"crossref","first-page":"11164","DOI":"10.1016\/j.eswa.2012.03.037","volume":"39","author":"J O\u00f1a De","year":"2012","unstructured":"De O\u00f1a J, De O\u00f1a R, Calvo FJ (2012) A classification tree approach to identify key factors of transit service quality. Expert Syst Appl 39:11164\u201311171","journal-title":"Expert Syst Appl"},{"key":"1573_CR8","doi-asserted-by":"crossref","first-page":"219","DOI":"10.1016\/j.tranpol.2013.07.001","volume":"29","author":"J O\u00f1a De","year":"2013","unstructured":"De O\u00f1a J, De O\u00f1a R, Eboli L, Mazzulla G (2013) Perceived service quality in bus transit service: a structural equation approach. Transp Policy 29:219\u2013226","journal-title":"Transp Policy"},{"key":"1573_CR9","doi-asserted-by":"crossref","first-page":"434","DOI":"10.1016\/j.aap.2005.06.024","volume":"38","author":"D Delen","year":"2006","unstructured":"Delen D, Sharda R, Bessonov M (2006) Identifying significant predictors of injury severity in traffic accidents using a series of artificial neural networks. Accid Anal Prev 38:434\u2013444","journal-title":"Accid Anal Prev"},{"issue":"6","key":"1573_CR10","doi-asserted-by":"crossref","first-page":"388","DOI":"10.1016\/j.tranpol.2010.04.006","volume":"17","author":"L Dell\u2019Olio","year":"2010","unstructured":"Dell\u2019Olio L, Ibeas A, Cec\u00edn P (2010) Modelling user perception of bus transit quality. Transp Policy 17(6):388\u2013397","journal-title":"Transp Policy"},{"issue":"1","key":"1573_CR11","doi-asserted-by":"crossref","first-page":"217","DOI":"10.1016\/j.tranpol.2010.08.005","volume":"18","author":"L Dell\u2019Olio","year":"2011","unstructured":"Dell\u2019Olio L, Ibeas A, Cec\u00edn P (2011) The quality of service desired by public transport users. Transp Policy 18(1):217\u2013227","journal-title":"Transp Policy"},{"key":"1573_CR12","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1007\/BF02309007","volume":"2","author":"Y Dimopoulos","year":"1995","unstructured":"Dimopoulos Y, Bourret P, Lek S (1995) Use of some sensitivity criteria for choosing networks with good generalization ability. Neural Process Lett 2:1\u20134","journal-title":"Neural Process Lett"},{"key":"1573_CR13","first-page":"107","volume":"38","author":"L Eboli","year":"2008","unstructured":"Eboli L, Mazulla G (2008) Willingness-to-pay of public transport users for improvement in service quality. Eur Transp 38:107\u2013118","journal-title":"Eur Transp"},{"key":"1573_CR14","doi-asserted-by":"crossref","first-page":"435","DOI":"10.1080\/01441640903068441","volume":"30","author":"L Eboli","year":"2010","unstructured":"Eboli L, Mazulla G (2010) How to capture the passengers\u2019 point of view on a transit service through rating and choice opinions. Transp Rev 30:435\u2013450","journal-title":"Transp Rev"},{"key":"1573_CR15","unstructured":"Engelbrecht AP, Cloete I, Zurada JM (1995) Determining the significance of input parameters using sensitivity analysis, from natural to artificial neural computation. In: proceedings of International Workshop on Artificial Neural Networks. M\u00e1laga-Torremolinos, Springer, Spain, pp 382\u2013388"},{"key":"1573_CR16","doi-asserted-by":"crossref","first-page":"183","DOI":"10.1016\/0893-6080(89)90003-8","volume":"2","author":"KI Funahashi","year":"1989","unstructured":"Funahashi KI (1989) On the approximate realization of continuous mappings by neural networks. Neural Netw 2:183\u2013192","journal-title":"Neural Netw"},{"key":"1573_CR17","first-page":"47","volume":"6","author":"GD Garson","year":"1991","unstructured":"Garson GD (1991) Interpreting neural-network connection weights. Artif Intell Expert 6:47\u201351","journal-title":"Artif Intell Expert"},{"key":"1573_CR18","doi-asserted-by":"crossref","unstructured":"Gedeon, T.D., Wong, P.M. & Harris, D., (1995). Balancing the bias and variance: network topology and pattern set reduction techniques. In: proceedings of International Workshop on Artificial Neural Networks, IWANN95, Torremolinos, Espa\u00f1a, pp 550\u2013558","DOI":"10.1007\/3-540-59497-3_222"},{"issue":"2","key":"1573_CR19","doi-asserted-by":"crossref","first-page":"209","DOI":"10.1142\/S0129065797000227","volume":"8","author":"TD Gedeon","year":"1997","unstructured":"Gedeon TD (1997) Data mining of inputs: analyzing magnitude of functional measures. Int J Neural Syst 8(2):209\u2013218","journal-title":"Int J Neural Syst"},{"key":"1573_CR20","doi-asserted-by":"crossref","first-page":"249","DOI":"10.1016\/S0304-3800(02)00257-0","volume":"160","author":"M Gevrey","year":"2003","unstructured":"Gevrey M, Dimopoulos I, Lek S (2003) Review and comparison of methods to study the contribution of variables in artificial neural network models. Ecol Model 160:249\u2013264","journal-title":"Ecol Model"},{"key":"1573_CR21","doi-asserted-by":"crossref","first-page":"43","DOI":"10.1016\/j.ecolmodel.2005.11.008","volume":"195","author":"M Gevrey","year":"2006","unstructured":"Gevrey M, Dimopoulos I, Lek S (2006) Two-way interaction of input variables in the sensitivity analysis of neural network models. Ecol Model 195:43\u201350","journal-title":"Ecol Model"},{"key":"1573_CR22","doi-asserted-by":"crossref","first-page":"143","DOI":"10.1016\/0954-1810(94)00011-S","volume":"9","author":"ATC Goh","year":"1995","unstructured":"Goh ATC (1995) Back-propagation neural networks for modeling complex systems. Artif Intell Eng 9:143\u2013151","journal-title":"Artif Intell Eng"},{"key":"1573_CR23","isbn-type":"print","volume-title":"Neural network design","author":"MT Hagan","year":"1996","unstructured":"Hagan MT, Demuth HB, Beale MH (1996) Neural network design. Campus Publishing Service, Colorado University Bookstore, Colorado. ISBN 0-9717321-0-8","ISBN":"https:\/\/id.crossref.org\/isbn\/0971732108"},{"key":"1573_CR24","unstructured":"He F, Sung AH, Guo B (1997) A neural network for prediction of oil well cement bonding quality. In: proceedings of IASTED international conference on control, IASTED-ACTA Press, Cancun-Mexico, pp 417\u2013420"},{"key":"1573_CR25","doi-asserted-by":"crossref","first-page":"11","DOI":"10.1016\/S0169-2607(99)00046-2","volume":"62","author":"A Hunter","year":"2000","unstructured":"Hunter A, Kennedy L, Henry J, Ferguson I (2000) Application of neural networks and sensitivity analysis to improved prediction of trauma survival. Comput Methods Progr Biomed 62:11\u201319","journal-title":"Comput Methods Progr Biomed"},{"key":"1573_CR26","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, Stichcombe M, White H (1989) Multilayer feedforward networks are universal approximators. Neural Netw 2:359\u2013366","journal-title":"Neural Netw"},{"key":"1573_CR27","doi-asserted-by":"crossref","first-page":"326","DOI":"10.1016\/j.ecolmodel.2007.01.009","volume":"204","author":"SL Kemp","year":"2007","unstructured":"Kemp SL, Zaradic P, Hansen F (2007) An approach for determining relative input parameter importance and significance in artificial neural networks. Ecol Model 204:326\u2013334","journal-title":"Ecol Model"},{"issue":"3","key":"1573_CR28","doi-asserted-by":"crossref","first-page":"668","DOI":"10.1109\/72.846738","volume":"11","author":"R Kewley","year":"2000","unstructured":"Kewley R, Embrechts M, Breneman C (2000) Data strip mining for the virtual design of pharmaceuticals with neural networks. IEEE Trans Neural Netw 11(3):668\u2013679","journal-title":"IEEE Trans Neural Netw"},{"issue":"8","key":"1573_CR29","doi-asserted-by":"crossref","first-page":"1229","DOI":"10.1071\/MF9951229","volume":"46","author":"S Lek","year":"1995","unstructured":"Lek S, Beland A, Dimopoulos I, Lauga J, Moreau J (1995) Improved estimation, using neural networks, of the food consumption of fish populations. Mar Freshw Res 46(8):1229\u20131236","journal-title":"Mar Freshw Res"},{"key":"1573_CR30","doi-asserted-by":"crossref","first-page":"39","DOI":"10.1016\/0304-3800(95)00142-5","volume":"90","author":"S Lek","year":"1996","unstructured":"Lek S, Delacoste M, Baran P, Dimopoulos I, Lauga J, Aulagnier S (1996) Application of neural networks to modeling nonlinear relationships in ecology. Ecol Model 90:39\u201352","journal-title":"Ecol Model"},{"key":"1573_CR31","doi-asserted-by":"crossref","first-page":"23","DOI":"10.1051\/alr:1996004","volume":"9","author":"S Lek","year":"1996","unstructured":"Lek S, Beland A, Baran P, Dimopoulos I, Delacoste M (1996) Role of some environmental variables in trout abundance models using neural networks. Aquat Living Resour 9:23\u201329","journal-title":"Aquat Living Resour"},{"issue":"2","key":"1573_CR32","doi-asserted-by":"crossref","first-page":"190","DOI":"10.1109\/91.388173","volume":"3","author":"Y Lin","year":"1995","unstructured":"Lin Y, Cunningham GA (1995) A new approach to fuzzy-neural system modeling. IEEE Trans Fuzzy Syst 3(2):190\u2013198","journal-title":"IEEE Trans Fuzzy Syst"},{"key":"1573_CR33","unstructured":"Mart\u00edn del B\u00edo B, Sanz Molina A (2006) Neural networks and fuzzy systems. Editorial RA-MA"},{"key":"1573_CR34","volume-title":"Practical neural networks recipes in C\u00a0++","author":"T Masters","year":"1993","unstructured":"Masters T (1993) Practical neural networks recipes in C\u00a0++. Academic Press, Waltham"},{"key":"1573_CR35","first-page":"1","volume":"9","author":"FR Moghaddam","year":"2010","unstructured":"Moghaddam FR, Afandizadeh S, Ziyadi M (2010) Prediction of accident severity using artificial neural networks. Int J Civ Eng 9:1","journal-title":"Int J Civ Eng"},{"key":"1573_CR36","doi-asserted-by":"crossref","first-page":"314","DOI":"10.1016\/j.aap.2008.12.008","volume":"41","author":"AH Mohammadipour","year":"2009","unstructured":"Mohammadipour AH, Alavi SH (2009) The optimization of the geometric cross-section dimensions of raised pedestrian crosswalks: a case of study in Qazvin. Accid Anal Prev 41:314\u2013326","journal-title":"Accid Anal Prev"},{"key":"1573_CR37","doi-asserted-by":"crossref","first-page":"705","DOI":"10.1016\/S0001-4575(99)00031-7","volume":"31","author":"L Mussone","year":"1999","unstructured":"Mussone L, Ferrari A, Oneta M (1999) An analysis of urban collisions using an artificial intelligence model. Accid Anal Prev 31:705\u2013718","journal-title":"Accid Anal Prev"},{"key":"1573_CR38","doi-asserted-by":"crossref","first-page":"135","DOI":"10.1016\/S0304-3800(02)00064-9","volume":"154","author":"JD Olden","year":"2002","unstructured":"Olden JD, Jackson DA (2002) Illuminating the \u201cblack-box\u201d: a randomization approach for understanding variable contributions in artificial neural networks. Ecol Model 154:135\u2013150","journal-title":"Ecol Model"},{"key":"1573_CR39","doi-asserted-by":"crossref","first-page":"389","DOI":"10.1016\/j.ecolmodel.2004.03.013","volume":"178","author":"JD Olden","year":"2004","unstructured":"Olden JD, Joy MK, Death RG (2004) An accurate comparison of methods for quantifying variable importance in artificial neural networks using simulated data. Ecol Model 178:389\u2013397","journal-title":"Ecol Model"},{"key":"1573_CR40","doi-asserted-by":"crossref","first-page":"15","DOI":"10.1016\/S0304-3800(98)00149-5","volume":"116","author":"SL \u00d6zesmi","year":"1999","unstructured":"\u00d6zesmi SL, \u00d6zesmi U (1999) An artificial neural network approach to spatial habitat modeling with interspecific interaction. Ecol Model 116:15\u201331","journal-title":"Ecol Model"},{"key":"1573_CR41","doi-asserted-by":"crossref","first-page":"3690","DOI":"10.1016\/j.asoc.2011.01.040","volume":"11","author":"M Paliwal","year":"2011","unstructured":"Paliwal M, Kumar UA (2011) Assessing the contribution of variables in feed forward neural network. Appl Soft Comput 11:3690\u20133696","journal-title":"Appl Soft Comput"},{"key":"1573_CR42","unstructured":"Palmer A, Monta\u00f1o JJ (2002a) Redes neuronales artificiales aplicadas al an\u00e1lisis de datos. Doctoral Dissertation. University of Palma de Mallorca"},{"issue":"1","key":"1573_CR43","first-page":"77","volume":"4","author":"A Palmer","year":"2002","unstructured":"Palmer A, Monta\u00f1o JJ (2002) Redes neuronales artificiales: abriendo la caja negra. Metodolog\u00eda de las ciencias del comportamiento 4(1):77\u201393","journal-title":"Metodolog\u00eda de las ciencias del comportamiento"},{"key":"1573_CR44","doi-asserted-by":"crossref","first-page":"119","DOI":"10.1007\/s00521-003-0377-9","volume":"12","author":"A Palmer","year":"2003","unstructured":"Palmer A, Monta\u00f1o JJ (2003) Numeric sensitivity analysis applied to feed forward neural networks. Neural Comput Appl 12:119\u2013125","journal-title":"Neural Comput Appl"},{"key":"1573_CR45","doi-asserted-by":"crossref","DOI":"10.1007\/978-1-4612-1746-6","volume-title":"Neural network data analysis using simulnet","author":"EJ Rzempoluk","year":"1998","unstructured":"Rzempoluk EJ (1998) Neural network data analysis using simulnet. Springer, New York"},{"key":"1573_CR46","doi-asserted-by":"crossref","DOI":"10.7551\/mitpress\/5236.001.0001","volume-title":"Parallel distributed processing, vol 1: foundations","author":"DE Rumelhart","year":"1986","unstructured":"Rumelhart DE, McClelland JL (1986) Parallel distributed processing, vol 1: foundations. MIT Press, Cambridge"},{"key":"1573_CR47","doi-asserted-by":"crossref","first-page":"533","DOI":"10.1038\/323533a0","volume":"323","author":"DE Rumelhart","year":"1986","unstructured":"Rumelhart DE, Hinton GE, Williams RJ (1986) Learning representations by backpropagation errors. Nature 323:533\u2013536","journal-title":"Nature"},{"issue":"2\u20133","key":"1573_CR48","doi-asserted-by":"crossref","first-page":"213","DOI":"10.1016\/S0304-3800(99)00103-9","volume":"120","author":"M Scardi","year":"1999","unstructured":"Scardi M, Harding LW (1999) Developing an empirical model of phytoplankton primary production: a neural networks case study. Ecol Model 120(2\u20133):213\u2013223","journal-title":"Ecol Model"},{"key":"1573_CR49","doi-asserted-by":"crossref","first-page":"405","DOI":"10.1016\/S0957-4174(98)00041-4","volume":"15","author":"AH Sung","year":"1998","unstructured":"Sung AH (1998) Ranking importance of input parameters of neural networks. Expert Syst Appl 15:405\u2013411","journal-title":"Expert Syst Appl"},{"key":"1573_CR50","doi-asserted-by":"crossref","first-page":"64","DOI":"10.1016\/j.ecoinf.2007.06.004","volume":"3","author":"MJ Watts","year":"2008","unstructured":"Watts MJ, Worner SP (2008) Using artificial neural networks to determine the relative contribution of abiotic factors influencing the establishment of insect pest species. Ecol Inform 3:64\u201374","journal-title":"Ecol Inform"},{"key":"1573_CR51","unstructured":"Werbos PJ (1974) Beyond regression: new tools for prediction and analysis in behavioral sciences. Doctoral Dissertation. Applied Mathematics, Harvard University"},{"key":"1573_CR52","first-page":"843","volume":"14","author":"J Yao","year":"1998","unstructured":"Yao J, Teng N, Poh HL, Tan CL (1998) Forecasting and analysis of marketing data using neural networks. J Inf Sci Eng 14:843\u2013862","journal-title":"J Inf Sci Eng"},{"key":"1573_CR53","doi-asserted-by":"crossref","first-page":"2225","DOI":"10.1016\/j.neucom.2010.01.011","volume":"73","author":"I Yeh","year":"2010","unstructured":"Yeh I, Cheng W (2010) First and second order sensitivity analysis of MLP. Neurocomputing 73:2225\u20132233","journal-title":"Neurocomputing"},{"issue":"1\u20132","key":"1573_CR54","doi-asserted-by":"crossref","first-page":"239","DOI":"10.1016\/S0004-3702(02)00190-X","volume":"137","author":"ZH Zhou","year":"2002","unstructured":"Zhou ZH, Wu J, Tang W (2002) Ensembling neural networks: many could be better than all. Artif Intell 137(1\u20132):239\u2013263","journal-title":"Artif Intell"},{"key":"1573_CR55","unstructured":"Zurada JM, Malinowski A, Cloete I (1994) Sensitivity analysis for minimization of input data dimensi\u00f3n for feed forward neural network. In: proceedings of IEEE international symposium on circuits and systems, IEEE Press, London"}],"container-title":["Neural Computing and Applications"],"original-title":[],"language":"en","link":[{"URL":"http:\/\/link.springer.com\/content\/pdf\/10.1007\/s00521-014-1573-5.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"http:\/\/link.springer.com\/article\/10.1007\/s00521-014-1573-5\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"http:\/\/link.springer.com\/content\/pdf\/10.1007\/s00521-014-1573-5","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2020,8,16]],"date-time":"2020-08-16T17:47:52Z","timestamp":1597600072000},"score":1,"resource":{"primary":{"URL":"http:\/\/link.springer.com\/10.1007\/s00521-014-1573-5"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2014,3,23]]},"references-count":55,"journal-issue":{"issue":"3-4","published-print":{"date-parts":[[2014,9]]}},"alternative-id":["1573"],"URL":"https:\/\/doi.org\/10.1007\/s00521-014-1573-5","relation":{},"ISSN":["0941-0643","1433-3058"],"issn-type":[{"value":"0941-0643","type":"print"},{"value":"1433-3058","type":"electronic"}],"subject":[],"published":{"date-parts":[[2014,3,23]]}}}