{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,28]],"date-time":"2026-04-28T10:25:20Z","timestamp":1777371920298,"version":"3.51.4"},"reference-count":26,"publisher":"Springer Science and Business Media LLC","issue":"3","license":[{"start":{"date-parts":[[2018,9,24]],"date-time":"2018-09-24T00:00:00Z","timestamp":1537747200000},"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":["Cent Eur J Oper Res"],"published-print":{"date-parts":[[2019,9]]},"DOI":"10.1007\/s10100-018-0586-z","type":"journal-article","created":{"date-parts":[[2018,9,24]],"date-time":"2018-09-24T11:11:58Z","timestamp":1537787518000},"page":"783-795","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":8,"title":["Application of different radial basis function networks in the illegal waste dump-surface modelling"],"prefix":"10.1007","volume":"27","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-0914-9595","authenticated-orcid":false,"given":"Polona","family":"Pavlov\u010di\u010d-Pre\u0161eren","sequence":"first","affiliation":[]},{"given":"Bojan","family":"Stopar","sequence":"additional","affiliation":[]},{"given":"Oskar","family":"Sterle","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2018,9,24]]},"reference":[{"issue":"40","key":"586_CR1","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1186\/2052-336X-12-40","volume":"12","author":"Z Abyaneh","year":"2014","unstructured":"Abyaneh Z (2014) Evaluation of multivariate linear regression and artificial neural networks in prediction of water quality parameters. J Environ Health Sci 12(40):1\u20138. \n                    https:\/\/doi.org\/10.1186\/2052-336X-12-40","journal-title":"J Environ Health Sci"},{"issue":"1\u20134","key":"586_CR2","doi-asserted-by":"publisher","first-page":"28","DOI":"10.1016\/j.jhydrol.2011.06.013","volume":"407","author":"J Adamowski","year":"2011","unstructured":"Adamowski J, Chan HF (2011) A wavelet neural network conjunction model for groundwater level forecasting. J Hydrol 407(1\u20134):28\u201340. \n                    https:\/\/doi.org\/10.1016\/j.jhydrol.2011.06.013","journal-title":"J Hydrol"},{"issue":"4","key":"586_CR3","first-page":"414","volume":"47","author":"S Berk","year":"2003","unstructured":"Berk S, Komadina \u017d, Marjanovi\u0107 M, Radovan D, Stopar B (2003) Combined solution of the EUREF GPS campaigns on the territory of Slovenia (in Slovene). Geod Vestn 47(4):414\u2013422","journal-title":"Geod Vestn"},{"key":"586_CR4","first-page":"321","volume":"2","author":"DS Broomhead","year":"1988","unstructured":"Broomhead DS, Lowe D (1988) Multivariable functional interpolation and adaptive networks. Compl Syst 2:321\u2013355","journal-title":"Compl Syst"},{"issue":"4","key":"586_CR5","doi-asserted-by":"publisher","first-page":"521","DOI":"10.1111\/j.1467-9671.2005.00233.x","volume":"9","author":"BH Carlisle","year":"2005","unstructured":"Carlisle BH (2005) Modelling the spatial distribution of DEM error. T GIS 9(4):521\u2013540. \n                    https:\/\/doi.org\/10.1111\/j.1467-9671.2005.00233.x","journal-title":"T GIS"},{"issue":"2","key":"586_CR6","doi-asserted-by":"publisher","first-page":"302","DOI":"10.1109\/72.80341","volume":"2","author":"S Chen","year":"1991","unstructured":"Chen S, Cowan CFN, Grant PM (1991) Orthogonal least squares learning algorithm for radial basis function networks. IEEE Trans Neural Netw 2(2):302\u2013309. \n                    https:\/\/doi.org\/10.1109\/72.80341","journal-title":"IEEE Trans Neural Netw"},{"key":"586_CR7","unstructured":"Costa JP, Pronzato L and Thierry E (2000) A comparison between kriging and radial basis function networks for nonlinear prediction. \n                    https:\/\/www.eurasip.org\/Proceedings\/Ext\/NSIP99\/Nsip99\/papers\/155.pdf\n                    \n                  . Accessed 15 March 2018"},{"key":"586_CR8","volume-title":"Neural networks and statistical learning","author":"KI Du","year":"2013","unstructured":"Du KI, Swamy NS (2013) Neural networks and statistical learning. Springer, London"},{"key":"586_CR9","doi-asserted-by":"publisher","first-page":"95","DOI":"10.1016\/j.cageo.2012.09.010","volume":"52","author":"B Erol","year":"2013","unstructured":"Erol B, Erol S (2013) Learning-based computing techniques in geoid modelling from precise height transformation. Comput Geosci 52:95\u2013107. \n                    https:\/\/doi.org\/10.1016\/j.cageo.2012.09.010","journal-title":"Comput Geosci"},{"issue":"1","key":"586_CR10","doi-asserted-by":"publisher","first-page":"24","DOI":"10.1109\/TNN.2004.836233","volume":"16","author":"S Ferrari","year":"2005","unstructured":"Ferrari S, Stengel RF (2005) Smooth function approximation using neural networks. IEEE Trans Neural Netw 16(1):24\u201338. \n                    https:\/\/doi.org\/10.1109\/TNN.2004.836233","journal-title":"IEEE Trans Neural Netw"},{"issue":"2","key":"586_CR11","doi-asserted-by":"publisher","first-page":"277","DOI":"10.1007\/s10100-011-0234-3","volume":"21","author":"S Giebel","year":"2013","unstructured":"Giebel S, Rainer M (2013) Neural network calibrated stochastic processes: forecasting financial assets. Cent Eur J Oper Res 21(2):277\u2013293. \n                    https:\/\/doi.org\/10.1007\/s10100-011-0234-3","journal-title":"Cent Eur J Oper Res"},{"issue":"5","key":"586_CR12","doi-asserted-by":"publisher","first-page":"387","DOI":"10.14358\/PERS.81.5.387","volume":"81","author":"CP Gillin","year":"2015","unstructured":"Gillin CP, Bailey SW, McGuire KJ, Prisley SP (2015) Evaluation of Lidar-derived DEMs through terrain analysis and field comparison. Photogramm Eng Rem Sens 81(5):387\u2013396. \n                    https:\/\/doi.org\/10.14358\/pers.81.5.387","journal-title":"Photogramm Eng Rem Sens"},{"issue":"2","key":"586_CR13","first-page":"108","volume":"8","author":"Y Harkouss","year":"2011","unstructured":"Harkouss Y, Fahs W, Ayache M (2011) A new algorithm for structure optimization of wavelet neural networks. Int J Comput Sci Issues 8(2):108\u2013117","journal-title":"Int J Comput Sci Issues"},{"key":"586_CR14","unstructured":"H\u00f6hle J, Potuckova M (2011) Assessment of the quality of digital terrain models. European Spatial Data Research, Frankfurt, Report No. 60"},{"issue":"5","key":"586_CR15","doi-asserted-by":"publisher","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(5):359\u2013366. \n                    https:\/\/doi.org\/10.1016\/0893-6080(89)90020-8n","journal-title":"Neural Netw"},{"issue":"B1","key":"586_CR16","doi-asserted-by":"publisher","first-page":"893","DOI":"10.5194\/isprsarchives-XLI-B1-893-2016","volume":"41","author":"M Kosmatin-Fras","year":"2016","unstructured":"Kosmatin-Fras M, Kerin A, Mesari\u010d M, Peterman V, Grigillo D (2016) Assessment of the quality of digital terrain model produced from unmanned aerial system imagery. Int Soc Photogramm Spatial Inf Sci 41(B1):893\u2013899. \n                    https:\/\/doi.org\/10.5194\/isprsarchives-XLI-B1-893-2016","journal-title":"Int Soc Photogramm Spatial Inf Sci"},{"issue":"3","key":"586_CR17","doi-asserted-by":"publisher","first-page":"389","DOI":"10.1007\/s40092-016-0146-x","volume":"12","author":"AP Markopoulos","year":"2016","unstructured":"Markopoulos AP, Georgiopoulos S, Manolakos DE (2016) On the use of back propagation and radial basis function neural networks in surface roughness prediction. J Ind Eng Int 12(3):389\u2013400. \n                    https:\/\/doi.org\/10.1007\/s40092-016-0146-x","journal-title":"J Ind Eng Int"},{"key":"586_CR18","unstructured":"MATLAB and Statistics Toolbox Release (2015b) The MathWorks Inc. Natick, Massachusetts"},{"issue":"3","key":"586_CR19","doi-asserted-by":"publisher","first-page":"606","DOI":"10.1162\/neco.1995.7.3.606","volume":"7","author":"M Orr","year":"1995","unstructured":"Orr M (1995) Regularization in the selection of radial basis function centers. Neural Comput 7(3):606\u2013623","journal-title":"Neural Comput"},{"issue":"5","key":"586_CR20","doi-asserted-by":"publisher","first-page":"2526","DOI":"10.1016\/j.asoc.2012.11.034","volume":"13","author":"P Pavlov\u010di\u010d-Pre\u0161eren","year":"2013","unstructured":"Pavlov\u010di\u010d-Pre\u0161eren P, Stopar B (2013) Wavelet neural network employment for continuous GNSS orbit function construction: application for the assisted-GNSS principle. Appl Soft Comput 13(5):2526\u20132536. \n                    https:\/\/doi.org\/10.1016\/j.asoc.2012.11.034","journal-title":"Appl Soft Comput"},{"key":"586_CR21","unstructured":"Pribi\u010devi\u0107 B (2000) The use of geologica l, geophysical and geodetical databases in determination of the shape of geoid in the Republic of Slovenia. Dissertation, University of Ljubljana"},{"issue":"8","key":"586_CR22","doi-asserted-by":"publisher","first-page":"187","DOI":"10.5194\/isprsannals-II-8-187-2014","volume":"2","author":"YS Rao","year":"2014","unstructured":"Rao YS, Deo R, Nalini J, Pillai AM, Muralikrishnan S, Dadhwal VK (2014) Quality assessment of TanDEM-X DEMs using airborne LiDAR, photogrammetry and ICESat elevation data. ISPRS Ann Photogramm Remote Sens Spatial Inf Sci 2(8):187\u2013192. \n                    https:\/\/doi.org\/10.5194\/isprsannals-II-8-187-2014","journal-title":"ISPRS Ann Photogramm Remote Sens Spatial Inf Sci"},{"issue":"2","key":"586_CR23","doi-asserted-by":"publisher","first-page":"105","DOI":"10.1061\/(ASCE)0887-3801(2004)18:2(105)","volume":"18","author":"MA Shahin","year":"2004","unstructured":"Shahin MA, Maier HR, Jaksa MB (2004) Data division for developing neural networks applied to geotechnical engineering. J Comput Civ Eng ASCE 18(2):105\u2013114","journal-title":"J Comput Civ Eng ASCE"},{"issue":"2","key":"586_CR24","first-page":"4","volume":"4","author":"Singh MK Snehmani","year":"2013","unstructured":"Snehmani Singh MK, Gupta RD, Ganju A (2013) DTM generation and avalanche hazard mapping using large format digital photogrammetric data and geomatics technique. J Remote Sens GIS 4(2):4\u201313","journal-title":"J Remote Sens GIS"},{"issue":"11","key":"586_CR25","doi-asserted-by":"publisher","first-page":"1265","DOI":"10.14358\/PERS.72.11.1265","volume":"72","author":"J Su","year":"2006","unstructured":"Su J, Bork E (2006) Influence of vegetation, slope, and LiDAR sampling angle on DEM accuracy. Photogramm Eng Rem Sens 72(11):1265\u20131274","journal-title":"Photogramm Eng Rem Sens"},{"key":"586_CR26","unstructured":"Zainuddin Z, Ong P (2007) Function approximation using artificial neural networks. Int J Syst Appl Eng Dev 4(1):173\u2013178. \n                    http:\/\/www.naun.org\/main\/UPress\/saed\/saed-23.pdf\n                    \n                  . Accessed 15 March 2018"}],"container-title":["Central European Journal of Operations Research"],"original-title":[],"language":"en","link":[{"URL":"http:\/\/link.springer.com\/content\/pdf\/10.1007\/s10100-018-0586-z.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"http:\/\/link.springer.com\/article\/10.1007\/s10100-018-0586-z\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"http:\/\/link.springer.com\/content\/pdf\/10.1007\/s10100-018-0586-z.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2019,9,23]],"date-time":"2019-09-23T19:17:20Z","timestamp":1569266240000},"score":1,"resource":{"primary":{"URL":"http:\/\/link.springer.com\/10.1007\/s10100-018-0586-z"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2018,9,24]]},"references-count":26,"journal-issue":{"issue":"3","published-print":{"date-parts":[[2019,9]]}},"alternative-id":["586"],"URL":"https:\/\/doi.org\/10.1007\/s10100-018-0586-z","relation":{},"ISSN":["1435-246X","1613-9178"],"issn-type":[{"value":"1435-246X","type":"print"},{"value":"1613-9178","type":"electronic"}],"subject":[],"published":{"date-parts":[[2018,9,24]]},"assertion":[{"value":"24 September 2018","order":1,"name":"first_online","label":"First Online","group":{"name":"ArticleHistory","label":"Article History"}}]}}