{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2024,9,9]],"date-time":"2024-09-09T20:33:06Z","timestamp":1725913986174},"publisher-location":"Cham","reference-count":10,"publisher":"Springer International Publishing","isbn-type":[{"type":"print","value":"9783319700922"},{"type":"electronic","value":"9783319700939"}],"license":[{"start":{"date-parts":[[2017,1,1]],"date-time":"2017-01-01T00:00:00Z","timestamp":1483228800000},"content-version":"unspecified","delay-in-days":0,"URL":"http:\/\/www.springer.com\/tdm"},{"start":{"date-parts":[[2017,1,1]],"date-time":"2017-01-01T00:00:00Z","timestamp":1483228800000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2017,1,1]],"date-time":"2017-01-01T00:00:00Z","timestamp":1483228800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2017]]},"DOI":"10.1007\/978-3-319-70093-9_13","type":"book-chapter","created":{"date-parts":[[2017,10,23]],"date-time":"2017-10-23T22:48:48Z","timestamp":1508798928000},"page":"120-130","update-policy":"http:\/\/dx.doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":1,"title":["Bayesian Curve Fitting Based on RBF Neural Networks"],"prefix":"10.1007","author":[{"given":"Michael","family":"Li","sequence":"first","affiliation":[]},{"given":"Santoso","family":"Wibowo","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2017,10,24]]},"reference":[{"volume-title":"Practical Handbook of Curve Fitting","year":"1994","author":"SL Arlinghaus","key":"13_CR1","unstructured":"Arlinghaus, S.L.: Practical Handbook of Curve Fitting. CRC Press, Boca Raton (1994)"},{"key":"13_CR2","volume-title":"Bayesian Data Analysis","author":"A Gelman","year":"2014","unstructured":"Gelman, A., et al.: Bayesian Data Analysis, 3rd edn. CRC Press, New York (2014)","edition":"3"},{"volume-title":"Pattern Recognition and Machine Learning","year":"2006","author":"CM Bishop","key":"13_CR3","unstructured":"Bishop, C.M.: Pattern Recognition and Machine Learning. Springer, Heidelberg (2006)"},{"issue":"2","key":"13_CR4","doi-asserted-by":"publisher","first-page":"333","DOI":"10.1111\/1467-9868.00128","volume":"B60","author":"DGT Denison","year":"1998","unstructured":"Denison, D.G.T., Mallick, B.K., Smith, A.F.M.: Automatic Bayesian curve fitting. J. R. Stat. Soc. B60(2), 333\u2013350 (1998)","journal-title":"J. R. Stat. Soc."},{"key":"13_CR5","doi-asserted-by":"publisher","first-page":"271","DOI":"10.1007\/s11222-008-9091-x","volume":"29","author":"C Chen","year":"2009","unstructured":"Chen, C., Yu, K.: Automatic Bayesian quantile regression curve fitting. Stat. Comput. 29, 271\u2013281 (2009)","journal-title":"Stat. Comput."},{"key":"13_CR6","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"},{"issue":"13","key":"13_CR7","doi-asserted-by":"publisher","first-page":"3066","DOI":"10.1016\/j.neucom.2009.03.016","volume":"72","author":"X Tang","year":"2009","unstructured":"Tang, X., Han, M.: Partial Lanczos extreme learning machine for single-output regression problem. Neurocomputing 72(13), 3066\u20133076 (2009)","journal-title":"Neurocomputing"},{"key":"13_CR8","doi-asserted-by":"publisher","first-page":"51","DOI":"10.1016\/0169-7439(86)80025-9","volume":"1","author":"L Chen","year":"1986","unstructured":"Chen, L., et al.: Effect of signal-to-noise and number of data points upon precision measure ment of peak amplitude, position and width in fourier transform spectrometry. Chemometr. Intell. Lab. Syst. 1, 51\u201358 (1986)","journal-title":"Chemometr. Intell. Lab. Syst."},{"key":"13_CR9","doi-asserted-by":"publisher","first-page":"299","DOI":"10.1016\/S0168-583X(01)00576-6","volume":"179","author":"H Paul","year":"2001","unstructured":"Paul, H., Schinner, A.: An empirical approach to the stopping power of solids and gases for ion Li to Ar. Nucl. Instrum. Methods Phys. Res. B 179, 299\u2013315 (2001)","journal-title":"Nucl. Instrum. Methods Phys. Res. B"},{"key":"13_CR10","first-page":"281","volume":"13","author":"J Bergstra","year":"2012","unstructured":"Bergstra, J., Benggio, Y.: Random search for hyperparameter optimization. J. Mach. Learn. Res. 13, 281\u2013305 (2012)","journal-title":"J. Mach. Learn. Res."}],"container-title":["Lecture Notes in Computer Science","Neural Information Processing"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/978-3-319-70093-9_13","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,3,13]],"date-time":"2024-03-13T16:20:37Z","timestamp":1710346837000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/978-3-319-70093-9_13"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2017]]},"ISBN":["9783319700922","9783319700939"],"references-count":10,"URL":"https:\/\/doi.org\/10.1007\/978-3-319-70093-9_13","relation":{},"ISSN":["0302-9743","1611-3349"],"issn-type":[{"type":"print","value":"0302-9743"},{"type":"electronic","value":"1611-3349"}],"subject":[],"published":{"date-parts":[[2017]]},"assertion":[{"value":"24 October 2017","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}},{"value":"ICONIP","order":1,"name":"conference_acronym","label":"Conference Acronym","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"International Conference on Neural Information Processing","order":2,"name":"conference_name","label":"Conference Name","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Guangzhou","order":3,"name":"conference_city","label":"Conference City","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"China","order":4,"name":"conference_country","label":"Conference Country","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"2017","order":5,"name":"conference_year","label":"Conference Year","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"14 November 2017","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"18 November 2017","order":8,"name":"conference_end_date","label":"Conference End Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"24","order":9,"name":"conference_number","label":"Conference Number","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"iconip2017","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"http:\/\/www.iconip2017.org\/index.html","order":11,"name":"conference_url","label":"Conference URL","group":{"name":"ConferenceInfo","label":"Conference Information"}}]}}