{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,2,21]],"date-time":"2025-02-21T03:21:17Z","timestamp":1740108077911,"version":"3.37.3"},"reference-count":37,"publisher":"Springer Science and Business Media LLC","issue":"4","license":[{"start":{"date-parts":[[2017,10,20]],"date-time":"2017-10-20T00:00:00Z","timestamp":1508457600000},"content-version":"unspecified","delay-in-days":0,"URL":"http:\/\/www.springer.com\/tdm"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["Neural Comput & Applic"],"published-print":{"date-parts":[[2018,8]]},"DOI":"10.1007\/s00521-017-3215-1","type":"journal-article","created":{"date-parts":[[2017,10,20]],"date-time":"2017-10-20T06:53:14Z","timestamp":1508482394000},"page":"1353-1368","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["Smooth statistical modeling of bivariate non-monotonic data by a three-stage LUT neural system"],"prefix":"10.1007","volume":"30","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-5964-7464","authenticated-orcid":false,"given":"Simone","family":"Fiori","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Nicola","family":"Fioranelli","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2017,10,20]]},"reference":[{"key":"3215_CR1","doi-asserted-by":"publisher","DOI":"10.1007\/s00521-016-2450-1","author":"Z Abdolahzare","year":"2016","unstructured":"Abdolahzare Z, Mehdizadeh SA (2016) Nonlinear mathematical modeling of seed spacing uniformity of a pneumatic planter using genetic programming and image processing. Neural Comput Appl. doi: 10.1007\/s00521-016-2450-1","journal-title":"Neural Comput Appl"},{"issue":"337","key":"3215_CR2","doi-asserted-by":"crossref","first-page":"140","DOI":"10.1080\/01621459.1972.10481216","volume":"67","author":"RE Barlow","year":"1972","unstructured":"Barlow RE, Brunk HD (1972) The isotonic regression problem and its dual. J Am Stat Assoc 67(337):140\u2013147","journal-title":"J Am Stat Assoc"},{"key":"3215_CR3","doi-asserted-by":"crossref","first-page":"151","DOI":"10.1093\/toxsci\/kfh007","volume":"77","author":"RB Conolly","year":"2003","unstructured":"Conolly RB, Lutz WK (2003) Nonmonotonic dose-response relationships: mechanistic basis, kinetic modeling, and implications for risk assessment. Toxicol Sci 77:151\u2013157","journal-title":"Toxicol Sci"},{"key":"3215_CR4","doi-asserted-by":"crossref","first-page":"19","DOI":"10.1007\/s00184-006-0084-5","volume":"66","author":"JS Dom\u00ednguez-Menchero","year":"2007","unstructured":"Dom\u00ednguez-Menchero JS, Gonz\u00e1lez-Rodr\u00edguez G (2007) Analyzing an extension of the isotonic regression problem. Metrika 66:19\u201330","journal-title":"Metrika"},{"issue":"3","key":"3215_CR5","doi-asserted-by":"crossref","first-page":"889","DOI":"10.1109\/TNN.2007.891679","volume":"18","author":"RW Duren","year":"2007","unstructured":"Duren RW, Marks RJ II, Reynolds PD, Trumbo ML (2007) Real-time neural network inversion on the SRC-6e reconfigurable computer. IEEE Trans Neural Netw 18(3):889\u2013901","journal-title":"IEEE Trans Neural Netw"},{"issue":"4","key":"3215_CR6","doi-asserted-by":"crossref","first-page":"583","DOI":"10.1007\/s00521-009-0318-3","volume":"19","author":"A El-Shafie","year":"2010","unstructured":"El-Shafie A, Abdelazim T, Noureldin A (2010) Neural network modeling of time-dependent creep deformations in masonry structures. Neural Comput Appl 19(4):583\u2013594","journal-title":"Neural Comput Appl"},{"key":"3215_CR7","doi-asserted-by":"crossref","first-page":"31","DOI":"10.1038\/464031b","volume":"464","author":"L Esaki","year":"2010","unstructured":"Esaki L, Arakawa Y, Kitamura M (2010) Esaki diode is still a radio star, half a century on. Nature 464:31","journal-title":"Nature"},{"issue":"2","key":"3215_CR8","doi-asserted-by":"crossref","first-page":"327","DOI":"10.1007\/s00521-012-1240-7","volume":"24","author":"F Evrendilek","year":"2014","unstructured":"Evrendilek F (2014) Assessing neural networks with wavelet denoising and regression models in predicting diel dynamics of eddy covariance-measured latent and sensible heat fluxes and evapotranspiration. Neural Comput Appl 24(2):327\u2013337","journal-title":"Neural Comput Appl"},{"issue":"10","key":"3215_CR9","doi-asserted-by":"crossref","first-page":"104202","DOI":"10.7498\/aps.60.104202","volume":"60","author":"Y-J Feng","year":"2011","unstructured":"Feng Y-J, Lin Z-X, Zhang R-Z (2011) The influence of root mean square phase gradient of continuous phase plate on smoothing focal spot. Acta Phys Sin 60(10):104202 (in Chinese)","journal-title":"Acta Phys Sin"},{"issue":"1","key":"3215_CR10","doi-asserted-by":"crossref","first-page":"85","DOI":"10.1016\/S0893-6080(01)00105-8","volume":"15","author":"S Fiori","year":"2002","unstructured":"Fiori S (2002) Hybrid independent component analysis by adaptive LUT activation function neurons. Neural Netw 15(1):85\u201394","journal-title":"Neural Netw"},{"key":"3215_CR11","doi-asserted-by":"crossref","first-page":"1367","DOI":"10.1007\/s00521-012-0958-6","volume":"22","author":"S Fiori","year":"2013","unstructured":"Fiori S (2013) Fast statistical regression in presence of a dominant independent variable. Neural Comput Appl 22:1367\u20131378","journal-title":"Neural Comput Appl"},{"key":"3215_CR12","doi-asserted-by":"crossref","first-page":"209","DOI":"10.1007\/s11634-013-0131-9","volume":"7","author":"S Fiori","year":"2013","unstructured":"Fiori S (2013) An isotonic trivariate statistical regression method. Adv Data Anal Classif 7:209\u2013235","journal-title":"Adv Data Anal Classif"},{"key":"3215_CR13","doi-asserted-by":"crossref","first-page":"708","DOI":"10.1049\/el.2014.0424","volume":"50","author":"S Fiori","year":"2014","unstructured":"Fiori S (2014) Fast closed-form trivariate statistical isotonic modeling. Electron Lett 50:708\u2013710","journal-title":"Electron Lett"},{"issue":"6","key":"3215_CR14","doi-asserted-by":"crossref","first-page":"715","DOI":"10.1007\/s12559-015-9353-9","volume":"7","author":"S Fiori","year":"2015","unstructured":"Fiori S, Gong T, Lee HK (2015) Bivariate non-isotonic statistical regression by a look-up table neural system. Cognit Comput 7(6):715\u2013730","journal-title":"Cognit Comput"},{"issue":"3","key":"3215_CR15","doi-asserted-by":"crossref","first-page":"351","DOI":"10.1111\/1467-9876.00074","volume":"46","author":"E Goetghebeur","year":"1997","unstructured":"Goetghebeur E, Lapp K (1997) The effect of treatment compliance in a placebo-controlled trial: regression with unpaired data. J R Stat Soc Ser C (Appl Stat) 46(3):351\u2013364","journal-title":"J R Stat Soc Ser C (Appl Stat)"},{"key":"3215_CR16","unstructured":"Gujarati DN, Porter DC (2009) Basic econometrics, 5th edn. McGraw-Hill, New York, pp 73 \u2013 78. ISBN: 978-0-07-337577-9"},{"issue":"1","key":"3215_CR17","doi-asserted-by":"crossref","first-page":"109","DOI":"10.1007\/s00521-011-0636-0","volume":"21","author":"WW Guo","year":"2012","unstructured":"Guo WW, Xue H (2012) An incorporative statistic and neural approach for crop yield modelling and forecasting. Neural Comput Appl 21(1):109\u2013117","journal-title":"Neural Comput Appl"},{"issue":"6","key":"3215_CR18","doi-asserted-by":"crossref","first-page":"761","DOI":"10.1007\/s00521-010-0495-0","volume":"20","author":"P H\u00e1jek","year":"2011","unstructured":"H\u00e1jek P, Olej V (2011) Credit rating modelling by kernel-based approaches with supervised and semi-supervised learning. Neural Comput Appl 20(6):761\u2013773","journal-title":"Neural Comput Appl"},{"key":"3215_CR19","doi-asserted-by":"crossref","unstructured":"Isermann R, M\u00fcnchhof M (2011) Neural networks and Lookup Tables for identification. In: Identification of dynamic systems\u2014an introduction with applications. Springer, Berlin, pp 501\u2013537. ISBN: 978-3-540-78878-2","DOI":"10.1007\/978-3-540-78879-9_20"},{"key":"3215_CR20","doi-asserted-by":"crossref","first-page":"372","DOI":"10.1109\/TPAMI.2004.1262333","volume":"26","author":"E Klassen","year":"2004","unstructured":"Klassen E, Srivastava A, Mio W (2004) Analysis of planar shapes using geodesic paths on shape spaces. IEEE Trans Pattern Anal Mach Intell 26:372\u2013383","journal-title":"IEEE Trans Pattern Anal Mach Intell"},{"key":"3215_CR21","doi-asserted-by":"crossref","unstructured":"Kot\u0142owski W, S\u0142owi\u0144ski R (2009) Rule learning with monotonicity constraints. In: Proceedings of the 26th international conference on machine learning (Montreal, Canada), pp 537\u2013544","DOI":"10.1145\/1553374.1553444"},{"key":"3215_CR22","doi-asserted-by":"publisher","unstructured":"Laudani A, Lozito GM, Riganti Fulginei F, Salvini A (2015) On training efficiency and computational costs of a feed forward neural network: a review. Comput Intell Neurosci. Article ID 818243. doi: 10.1155\/2015\/818243","DOI":"10.1155\/2015\/818243"},{"issue":"1","key":"3215_CR23","doi-asserted-by":"crossref","first-page":"192","DOI":"10.1080\/10618600.2012.741550","volume":"23","author":"R Luss","year":"2014","unstructured":"Luss R, Rosset S (2014) Generalized isotonic regression. J Comput Graph Stat 23(1):192\u2013210","journal-title":"J Comput Graph Stat"},{"issue":"5","key":"3215_CR24","first-page":"365","volume":"1","author":"HJ Motulsky","year":"1987","unstructured":"Motulsky HJ, Ransnas LA (1987) Fitting curves to data using nonlinear regression: a practical and nonmathematical review. Fed Am Soc Exp Biol (FASEB) J 1(5):365\u2013374","journal-title":"Fed Am Soc Exp Biol (FASEB) J"},{"issue":"1","key":"3215_CR25","doi-asserted-by":"crossref","first-page":"187","DOI":"10.1007\/s00521-012-0940-3","volume":"22","author":"A Najah","year":"2013","unstructured":"Najah A, El-Shafie A, Karim OA, El-Shafie AH (2013) Application of artificial neural networks for water quality prediction. Neural Comput Appl 22(1):187\u2013201","journal-title":"Neural Comput Appl"},{"key":"3215_CR26","doi-asserted-by":"crossref","unstructured":"Niu K, Zhao F, Qiao X (2013) A missing data imputation algorithm in wireless sensor network based on minimized similarity distortion. In: Proceedings of the sixth international symposium on computational intelligence and design (Hangzhou, People\u2019s Republic of China, October 28\u201329, 2013), vol 2, pp 235\u2013238","DOI":"10.1109\/ISCID.2013.172"},{"key":"3215_CR27","doi-asserted-by":"publisher","DOI":"10.1007\/s00521-016-2344-2","author":"TO Owolabi","year":"2016","unstructured":"Owolabi TO, Zakariya YF, Olatunji SO, Akande KO (2016) Estimation of melting points of fatty acids using homogeneously hybridized support vector regression. Neural Comput Appl. doi: 10.1007\/s00521-016-2344-2","journal-title":"Neural Comput Appl"},{"issue":"1","key":"3215_CR28","doi-asserted-by":"crossref","first-page":"41","DOI":"10.1007\/s00521-014-1696-8","volume":"26","author":"S Prabhu","year":"2015","unstructured":"Prabhu S, Uma M, Vinayagam BK (2015) Surface roughness prediction using Taguchi-fuzzy logic-neural network analysis for CNT nanofluids based grinding process. Neural Comp Appl 26(1):41\u201355","journal-title":"Neural Comp Appl"},{"issue":"4","key":"3215_CR29","doi-asserted-by":"crossref","first-page":"835","DOI":"10.1007\/s00521-016-2356-y","volume":"28","author":"F Sa\u00e2daoui","year":"2017","unstructured":"Sa\u00e2daoui F (2017) A seasonal feedforward neural network to forecast electricity prices. Neural Comput Appl 28(4):835\u2013847","journal-title":"Neural Comput Appl"},{"key":"3215_CR30","volume-title":"Data Model Essent","author":"G Simsion","year":"2005","unstructured":"Simsion G, Witt G (2005) Data Model Essent, 3rd edn. Morgan Kauffman Publishers, Los Altos","edition":"3"},{"key":"3215_CR31","volume-title":"Neural networks for statistical modeling","author":"M Smith","year":"1996","unstructured":"Smith M (1996) Neural networks for statistical modeling. International Thomson Computer Press, London"},{"issue":"6","key":"3215_CR32","doi-asserted-by":"crossref","first-page":"568","DOI":"10.1109\/72.97934","volume":"2","author":"DE Specht","year":"1991","unstructured":"Specht DE (1991) A general regression neural network. IEEE Trans Neural Netw 2(6):568\u2013576","journal-title":"IEEE Trans Neural Netw"},{"key":"3215_CR33","unstructured":"Tamminen S, Laurinen P, R\u00f6ning J (1999) Comparing regression trees with neural networks in aerobic fitness approximation. In: Proceedings of the international computing sciences conference symposium on advances in intelligent data analysis (Rochester, 1999), pp 414\u2013419"},{"issue":"1","key":"3215_CR34","doi-asserted-by":"crossref","first-page":"54","DOI":"10.1198\/TECH.2010.10111","volume":"53","author":"RJ Tibshirani","year":"2011","unstructured":"Tibshirani RJ, Hoefling H, Tibshirani R (2011) Nearly-isotonic regression. Technometrics 53(1):54\u201361","journal-title":"Technometrics"},{"key":"3215_CR35","unstructured":"Vansteenkiste E (2015) Lookup-table based neurons for an efficient FPGA implementation of neural networks. Master Thesis of the computing systems lab (CSL), Electronics and information systems (ELIS) department, Ghent University (Belgium)"},{"key":"3215_CR36","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1016\/j.jspi.2014.12.007","volume":"161","author":"J Wu","year":"2015","unstructured":"Wu J, Meyer MC, Opsomer JD (2015) Penalized isotonic regression. J Stat Plan Inference 161:1\u201324","journal-title":"J Stat Plan Inference"},{"issue":"1","key":"3215_CR37","doi-asserted-by":"crossref","first-page":"26","DOI":"10.1016\/j.aquaeng.2005.03.003","volume":"34","author":"R Yu","year":"2006","unstructured":"Yu R, Leung PS, Bienfang P (2006) Predicting shrimp growth: artificial neural network versus nonlinear regression models. Aquac Eng 34(1):26\u201332","journal-title":"Aquac Eng"}],"container-title":["Neural Computing and Applications"],"original-title":[],"language":"en","link":[{"URL":"http:\/\/link.springer.com\/article\/10.1007\/s00521-017-3215-1\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"http:\/\/link.springer.com\/content\/pdf\/10.1007\/s00521-017-3215-1.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"http:\/\/link.springer.com\/content\/pdf\/10.1007\/s00521-017-3215-1.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2022,8,4]],"date-time":"2022-08-04T22:58:45Z","timestamp":1659653925000},"score":1,"resource":{"primary":{"URL":"http:\/\/link.springer.com\/10.1007\/s00521-017-3215-1"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2017,10,20]]},"references-count":37,"journal-issue":{"issue":"4","published-print":{"date-parts":[[2018,8]]}},"alternative-id":["3215"],"URL":"https:\/\/doi.org\/10.1007\/s00521-017-3215-1","relation":{},"ISSN":["0941-0643","1433-3058"],"issn-type":[{"type":"print","value":"0941-0643"},{"type":"electronic","value":"1433-3058"}],"subject":[],"published":{"date-parts":[[2017,10,20]]}}}