{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,3,26]],"date-time":"2025-03-26T11:04:52Z","timestamp":1742987092052,"version":"3.40.3"},"publisher-location":"Cham","reference-count":15,"publisher":"Springer International Publishing","isbn-type":[{"type":"print","value":"9783319238616"},{"type":"electronic","value":"9783319238623"}],"license":[{"start":{"date-parts":[[2015,1,1]],"date-time":"2015-01-01T00:00:00Z","timestamp":1420070400000},"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":[],"published-print":{"date-parts":[[2015]]},"DOI":"10.1007\/978-3-319-23862-3_10","type":"book-chapter","created":{"date-parts":[[2015,10,13]],"date-time":"2015-10-13T14:06:06Z","timestamp":1444745166000},"page":"96-106","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":1,"title":["Auroral Oval Boundary Modeling Based on Deep Learning Method"],"prefix":"10.1007","author":[{"given":"Bing","family":"Han","sequence":"first","affiliation":[]},{"given":"Xinbo","family":"Gao","sequence":"additional","affiliation":[]},{"given":"Hui","family":"Liu","sequence":"additional","affiliation":[]},{"given":"Ping","family":"Wang","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2015,10,17]]},"reference":[{"issue":"4","key":"10_CR1","doi-asserted-by":"publisher","first-page":"273","DOI":"10.1016\/0032-0633(64)90151-5","volume":"12","author":"SI Akasofu","year":"1964","unstructured":"Akasofu, S.I.: The development of the auroralsubstorm. Planet. Space Sci. 12(4), 273\u2013282 (1964)","journal-title":"Planet. Space Sci."},{"key":"10_CR2","doi-asserted-by":"crossref","unstructured":"Carbary, J.F.: A Kp-based model of auroral boundaries. Space Weather, 3(10) (2005)","DOI":"10.1029\/2005SW000162"},{"issue":"2","key":"10_CR3","doi-asserted-by":"publisher","first-page":"209","DOI":"10.1016\/0032-0633(67)90190-0","volume":"15","author":"YI Feldstein","year":"1967","unstructured":"Feldstein, Y.I., Starkov, G.V.: Dynamics of auroral belt and polar geomagnetic disturbances. Planet. Space Sci. 15(2), 209\u2013229 (1967)","journal-title":"Planet. Space Sci."},{"key":"10_CR4","first-page":"331","volume":"34","author":"GV Starkov","year":"1994","unstructured":"Starkov, G.V.: Mathematical model of the auroral boundaries. Geomag. Aeron. 34, 331\u2013336 (1994)","journal-title":"Geomag. Aeron."},{"issue":"8","key":"10_CR5","doi-asserted-by":"publisher","first-page":"1231","DOI":"10.1016\/j.jastp.2008.03.008","volume":"70","author":"Y Zhang","year":"2008","unstructured":"Zhang, Y., Paxton, L.J.: An empirical Kp-dependent global auroral model based on TIMED\/GUVI FUV data. J. Atmos. Solar Terr. Phys. 70(8), 1231\u20131242 (2008)","journal-title":"J. Atmos. Solar Terr. Phys."},{"issue":"7","key":"10_CR6","doi-asserted-by":"publisher","first-page":"2913","DOI":"10.5194\/angeo-27-2913-2009","volume":"27","author":"SE Milan","year":"2009","unstructured":"Milan, S.E., Hutchinson, J., Boakes, P.D., Hubert, B.: Influences on the radius of the auroral oval. Annales Geophysicae 27(7), 2913\u20132924 (2009). Copernicus GmbH","journal-title":"Annales Geophysicae"},{"issue":"1","key":"10_CR7","doi-asserted-by":"publisher","first-page":"46","DOI":"10.1134\/S0010952513010061","volume":"51","author":"R Lukianova","year":"2013","unstructured":"Lukianova, R., Kozlovsky, A.: Dynamics of polar boundary of the auroral oval derived from the IMAGE satellite data. Cosm. Res. 51(1), 46\u201353 (2013)","journal-title":"Cosm. Res."},{"key":"10_CR8","unstructured":"Yang, Q.J.: Auroral Events Detection and Analysis Based on ASI and UVI Images. Ph.D. thesis (2013)"},{"key":"10_CR9","doi-asserted-by":"publisher","first-page":"1527","DOI":"10.1162\/neco.2006.18.7.1527","volume":"18","author":"GE Hinton","year":"2006","unstructured":"Hinton, G.E., Osindero, S., Teh, Y.: A fast learning algorithm for deep belief nets. Neural Comput. 18, 1527\u20131554 (2006)","journal-title":"Neural Comput."},{"key":"10_CR10","doi-asserted-by":"publisher","first-page":"145","DOI":"10.1109\/MSP.2010.939038","volume":"28","author":"Y Dong","year":"2011","unstructured":"Dong, Y., Li, D.: Deep learning and its applications to signal and information processing. IEEE Signal Process. Mag. 28, 145\u2013154 (2011)","journal-title":"IEEE Signal Process. Mag."},{"issue":"1","key":"10_CR11","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1561\/2200000006","volume":"2","author":"Y Bengio","year":"2009","unstructured":"Bengio, Y.: Learning deep architectures for AI. Mach. Learn. 2(1), 1\u2013127 (2009)","journal-title":"Mach. Learn."},{"key":"10_CR12","series-title":"Lecture Notes in Computer Science","doi-asserted-by":"publisher","first-page":"748","DOI":"10.1007\/978-3-642-42057-3_94","volume-title":"Intelligence Science and Big Data Engineering","author":"H Liu","year":"2013","unstructured":"Liu, H., Gao, X., Han, B., Yang, X.: An automatic MSRM method with a feedback based on shape information for auroral oval segmentation. In: Sun, C., Fang, F., Zhou, Z.-H., Yang, W., Liu, Z.-Y. (eds.) IScIDE 2013. LNCS, vol. 8261, pp. 748\u2013755. Springer, Heidelberg (2013)"},{"key":"10_CR13","doi-asserted-by":"publisher","first-page":"299","DOI":"10.1007\/s00466-003-0532-2","volume":"33","author":"S Lukaszyk","year":"2004","unstructured":"Lukaszyk, S.: A new concept of probability metric and its applications in approximation of scattered data sets. Comput. Mech. 33, 299\u2013304 (2004)","journal-title":"Comput. Mech."},{"issue":"8","key":"10_CR14","doi-asserted-by":"publisher","first-page":"1771","DOI":"10.1162\/089976602760128018","volume":"14","author":"G Hinton","year":"2002","unstructured":"Hinton, G.: A Practical Guide to Training products of experts by minimizing contrastive divergence. Neural Comput. 14(8), 1771\u20131800 (2002)","journal-title":"Neural Comput."},{"key":"10_CR15","unstructured":"OMNI dataset description: \n                    http:\/\/omniweb.gsfc.nasa.gov\/html\/HROdocum.html\n                    \n                  ."}],"container-title":["Lecture Notes in Computer Science","Intelligence Science and Big Data Engineering. Big Data and Machine Learning Techniques"],"original-title":[],"language":"en","link":[{"URL":"http:\/\/link.springer.com\/content\/pdf\/10.1007\/978-3-319-23862-3_10","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2019,5,31]],"date-time":"2019-05-31T01:49:29Z","timestamp":1559267369000},"score":1,"resource":{"primary":{"URL":"http:\/\/link.springer.com\/10.1007\/978-3-319-23862-3_10"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2015]]},"ISBN":["9783319238616","9783319238623"],"references-count":15,"URL":"https:\/\/doi.org\/10.1007\/978-3-319-23862-3_10","relation":{},"ISSN":["0302-9743","1611-3349"],"issn-type":[{"type":"print","value":"0302-9743"},{"type":"electronic","value":"1611-3349"}],"subject":[],"published":{"date-parts":[[2015]]},"assertion":[{"value":"17 October 2015","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}}]}}