{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2024,9,8]],"date-time":"2024-09-08T19:13:22Z","timestamp":1725822802655},"publisher-location":"Cham","reference-count":15,"publisher":"Springer International Publishing","isbn-type":[{"type":"print","value":"9783319192215"},{"type":"electronic","value":"9783319192222"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2015]]},"DOI":"10.1007\/978-3-319-19222-2_22","type":"book-chapter","created":{"date-parts":[[2015,6,5]],"date-time":"2015-06-05T03:01:02Z","timestamp":1433473262000},"page":"262-275","source":"Crossref","is-referenced-by-count":1,"title":["An Improved RBF Neural Network Approach to Nonlinear Curve Fitting"],"prefix":"10.1007","author":[{"given":"Michael M.","family":"Li","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Brijesh","family":"Verma","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2015,6,6]]},"reference":[{"key":"22_CR1","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., Stinchcomb, M., White, H.: Multilayer feedforward networks are universal approximators. Neural Networks 2, 359\u2013366 (1989)","journal-title":"Neural Networks"},{"key":"22_CR2","doi-asserted-by":"publisher","first-page":"246","DOI":"10.1162\/neco.1991.3.2.246","volume":"3","author":"J Park","year":"1991","unstructured":"Park, J., Sandberg, I.W.: Universal approximation using radial basis function. Neural Computation 3, 246\u2013257 (1991)","journal-title":"Neural Computation"},{"key":"22_CR3","doi-asserted-by":"publisher","first-page":"1481","DOI":"10.1109\/5.58326","volume":"78","author":"T Poggio","year":"1990","unstructured":"Poggio, T., Girosi, F.: Networks for approximation and learning. Proc. IEEE 78, 1481\u20131497 (1990)","journal-title":"Proc. IEEE"},{"key":"22_CR4","volume-title":"Ion beams for materials analysis","author":"JR Bird","year":"1989","unstructured":"Bird, J.R., Williams, J.S.: Ion beams for materials analysis. Academic Press, New York (1989)"},{"key":"22_CR5","doi-asserted-by":"publisher","first-page":"953","DOI":"10.1200\/JCO.2006.09.7816","volume":"25","author":"D Schulz-Ertner","year":"2007","unstructured":"Schulz-Ertner, D., Tsujii, H.: Particle radiation therapy using proton and heavier ion beams. J. Clin. Oncol. 25, 953\u2013964 (2007)","journal-title":"J. Clin. Oncol."},{"key":"22_CR6","volume-title":"SRIM - The Stopping and Range of Ions in Matter","author":"JF Ziegler","year":"2008","unstructured":"Ziegler, J.F., Biersack, J.P., Ziegler, M.D.: SRIM - The Stopping and Range of Ions in Matter. SRIM Co., Chester (2008)"},{"key":"22_CR7","doi-asserted-by":"publisher","first-page":"377","DOI":"10.1016\/j.adt.2003.08.003","volume":"85","author":"H Paul","year":"2003","unstructured":"Paul, H., Schinner, A.: Empirical stopping power tables for ions from 3Li to 18Ar and from 0.001 to 1000 MeV\/nucleon in solids and gases. Atomic Data and Nuclear Data Tables 85, 377\u2013452 (2003)","journal-title":"Atomic Data and Nuclear Data Tables"},{"key":"22_CR8","doi-asserted-by":"publisher","first-page":"106","DOI":"10.1016\/S0168-583X(98)00453-4","volume":"146","author":"G Konac","year":"1998","unstructured":"Konac, G., Klatt, Ch., Kalbitzer, S.: Universal fit formula for electronic stopping power of all ions in carbon and silicon. Nuclear Instruments and Methods in Physics Research B 146, 106\u2013113 (1998)","journal-title":"Nuclear Instruments and Methods in Physics Research B"},{"key":"22_CR9","unstructured":"Haykin, S.: Neural Networks: A Comprehensive Foundation, 2nd edn. Prentice Hall (1998)"},{"key":"22_CR10","doi-asserted-by":"publisher","first-page":"391","DOI":"10.1007\/s00521-007-0138-2","volume":"17","author":"MM Li","year":"2008","unstructured":"Li, M.M., Verma, B., Fan, X., Tickle, K.: RBF neural networks for solving the inverse problem of backscattering spectra. Neural Computing and Applications 17, 391\u2013399 (2008)","journal-title":"Neural Computing and Applications"},{"key":"22_CR11","doi-asserted-by":"publisher","first-page":"142","DOI":"10.1002\/9780470316719","volume-title":"Nonlinear statistical models","author":"AR Gallant","year":"1987","unstructured":"Gallant, A.R.: Nonlinear statistical models, pp. 142\u2013146. John Wiley, Canada (1987)"},{"key":"22_CR12","series-title":"Monograph on Numerical Analysis","doi-asserted-by":"crossref","DOI":"10.1093\/oso\/9780198534419.001.0001","volume-title":"Curve and surface fitting with splines","author":"P Dierckx","year":"1993","unstructured":"Dierckx, P.: Curve and surface fitting with splines. Monograph on Numerical Analysis. Clarendon Press, London (1993)"},{"key":"22_CR13","unstructured":"Gunn, S.R.: Support vector machine for classification and regression. Technical Report. University of Southhampton, UK (1998)"},{"key":"22_CR14","doi-asserted-by":"publisher","first-page":"34","DOI":"10.1016\/S0168-583X(00)00684-4","volume":"183","author":"Y Zhang","year":"2001","unstructured":"Zhang, Y., Possnert, G., Whitlow, H.J.: Measurement of the mean energy-loss of swift heavy ions in carbon with high precision. Nuclear Instruments and Methods in Physics Research B 183, 34\u201347 (2001)","journal-title":"Nuclear Instruments and Methods in Physics Research B"},{"key":"22_CR15","doi-asserted-by":"crossref","unstructured":"Li, M., Guo, W., Verma, B., Lee, H.: A neural networks-based fitting to high energy stopping power data for heavy ion in solid matter. In: Proceedings of WCCI 2012 IEEE, Brisbane, Australia, pp. 832\u2013837 (2012)","DOI":"10.1109\/IJCNN.2012.6252478"}],"container-title":["Lecture Notes in Computer Science","Advances in Computational Intelligence"],"original-title":[],"link":[{"URL":"http:\/\/link.springer.com\/content\/pdf\/10.1007\/978-3-319-19222-2_22","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,6,9]],"date-time":"2024-06-09T10:40:36Z","timestamp":1717929636000},"score":1,"resource":{"primary":{"URL":"http:\/\/link.springer.com\/10.1007\/978-3-319-19222-2_22"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2015]]},"ISBN":["9783319192215","9783319192222"],"references-count":15,"URL":"https:\/\/doi.org\/10.1007\/978-3-319-19222-2_22","relation":{},"ISSN":["0302-9743","1611-3349"],"issn-type":[{"type":"print","value":"0302-9743"},{"type":"electronic","value":"1611-3349"}],"subject":[],"published":{"date-parts":[[2015]]}}}