{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,8,27]],"date-time":"2025-08-27T16:09:00Z","timestamp":1756310940627},"publisher-location":"Cham","reference-count":16,"publisher":"Springer International Publishing","isbn-type":[{"type":"print","value":"9783030014179"},{"type":"electronic","value":"9783030014186"}],"license":[{"start":{"date-parts":[[2018,1,1]],"date-time":"2018-01-01T00:00:00Z","timestamp":1514764800000},"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":[],"published-print":{"date-parts":[[2018]]},"DOI":"10.1007\/978-3-030-01418-6_57","type":"book-chapter","created":{"date-parts":[[2018,9,26]],"date-time":"2018-09-26T14:57:36Z","timestamp":1537973856000},"page":"579-588","update-policy":"http:\/\/dx.doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":4,"title":["Estimation of Microphysical Parameters of Atmospheric Pollution Using Machine Learning"],"prefix":"10.1007","author":[{"given":"C.","family":"Llerena","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"D.","family":"M\u00fcller","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"R.","family":"Adams","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"N.","family":"Davey","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Y.","family":"Sun","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2018,9,27]]},"reference":[{"key":"57_CR1","doi-asserted-by":"crossref","unstructured":"Stocker, T.F., et al.: Climate change 2013: the physical science basis. Intergovernmental panel on climate change, working group I contribution to the IPCC fifth assessment report (AR5), Cambridge, UK and New York, NY, USA, p. 1535 (2013)","DOI":"10.1017\/CBO9781107415324"},{"key":"57_CR2","doi-asserted-by":"publisher","first-page":"105","DOI":"10.1007\/0-387-25101-4_4","volume-title":"Lidar","author":"A Ansmann","year":"2005","unstructured":"Ansmann, A., M\u00fcller, D.: Lidar and atmospheric aerosol particles. In: Weitkamp, C. (ed.) Lidar, pp. 105\u2013141. Springer, New York (2005). https:\/\/doi.org\/10.1007\/0-387-25101-4_4"},{"key":"57_CR3","doi-asserted-by":"publisher","first-page":"746","DOI":"10.1364\/OL.15.000746","volume":"15","author":"A Ansmann","year":"1990","unstructured":"Ansmann, A., Riebesell, M., Weitkamp, C.: Measurement of atmospheric aerosol extinction profiles with a Raman lidar. Opt. Lett. 15, 746\u2013748 (1990)","journal-title":"Opt. Lett."},{"issue":"18","key":"57_CR4","doi-asserted-by":"publisher","first-page":"3685","DOI":"10.1364\/AO.41.003685","volume":"41","author":"I Veselovskii","year":"2002","unstructured":"Veselovskii, I., Kolgotin, A., Griaznov, V., M\u00fcller, D., Wandinger, U., Whiteman, N.D.: Inversion with regularization for the retrieval of tropospheric aerosol parameters from multiwavelength lidar sounding. Appl. Opt. 41(18), 3685\u20133699 (2002)","journal-title":"Appl. Opt."},{"key":"57_CR5","doi-asserted-by":"publisher","first-page":"2358","DOI":"10.1364\/AO.38.002358","volume":"38","author":"D M\u00fcller","year":"1999","unstructured":"M\u00fcller, D., Wandinger, U., Ansmann, A.: Microphysical particle parameters from extinction and backscatter lidar data by inversion with regularization: simulation. Appl. Opt. 38, 2358\u20132368 (1999)","journal-title":"Appl. Opt."},{"key":"57_CR6","doi-asserted-by":"publisher","first-page":"518","DOI":"10.1364\/JOSAA.22.000518","volume":"22","author":"C B\u00f6ckmann","year":"2005","unstructured":"B\u00f6ckmann, C., Mironova, I., M\u00fcller, D., Schneidenbach, L., Nessler, R.: Microphysical aerosol parameters from multiwavelength lidar. J. Opt. Soc. Am. A 22, 518\u2013528 (2005)","journal-title":"J. Opt. Soc. Am. A"},{"key":"57_CR7","doi-asserted-by":"publisher","first-page":"4472","DOI":"10.1364\/AO.47.004472","volume":"47","author":"A Kolgotin","year":"2008","unstructured":"Kolgotin, A., M\u00fcller, D.: Theory of inversion with two-dimensional regularization: profiles of microphysical particle properties derived from multiwavelength lidar measurements. Appl. Opt. 47, 4472\u20134490 (2008)","journal-title":"Appl. Opt."},{"key":"57_CR8","doi-asserted-by":"publisher","first-page":"2069","DOI":"10.1364\/AO.50.002069","volume":"50","author":"D M\u00fcller","year":"2011","unstructured":"M\u00fcller, D., Kolgotin, A., Mattis, I., Petzold, A., Stohl, A.: Vertical profiles of microphysical particle properties derived from inversion with two-dimensional regularization of multiwavelength Raman lidar data: experiment. Appl. Opt. 50, 2069\u20132079 (2011)","journal-title":"Appl. Opt."},{"key":"57_CR9","doi-asserted-by":"crossref","unstructured":"Mamun, M.M., M\u00fcller, D.: Retrieval of Intensive aerosol microphysical parameters from multiwavelength Raman\/HSRL lidar: feasibility study with artificial neural networks. Neural Netw. Atmos. Meas. Tech. Discuss. 7 (2016)","DOI":"10.5194\/amt-2016-7"},{"key":"57_CR10","unstructured":"Hadamard, J.: Bull. Univ. Princeton 13, 49 (1902)"},{"key":"57_CR11","volume-title":"Artificial Neural Networks","author":"RJ Schalkoff","year":"1997","unstructured":"Schalkoff, R.J.: Artificial Neural Networks, vol. 1. McGraw-Hill, New York (1997)"},{"key":"57_CR12","doi-asserted-by":"publisher","DOI":"10.1002\/9783527618156","volume-title":"Absorption and Scattering of Light by Small Particles","author":"C Bohren","year":"1998","unstructured":"Bohren, C., Huffman, D.: Absorption and Scattering of Light by Small Particles. Wiley, Hoboken (1998). Wiley science paperback series"},{"key":"57_CR13","unstructured":"Hinds, C.W.: Aerosol Technology: Properties, Behavior, and Measurement of Airborne Particles, 2nd edn., p. 504, January 1999. ISBN 978-0-471-19410-1"},{"issue":"2","key":"57_CR14","doi-asserted-by":"publisher","first-page":"1883","DOI":"10.4249\/scholarpedia.1883","volume":"4","author":"LE Peterson","year":"2009","unstructured":"Peterson, L.E.: K-nearest neighbor. Scholarpedia 4(2), 1883 (2009)","journal-title":"Scholarpedia"},{"issue":"1\u20133","key":"57_CR15","doi-asserted-by":"publisher","first-page":"489","DOI":"10.1016\/j.neucom.2005.12.126","volume":"70","author":"G-B Huang","year":"2006","unstructured":"Huang, G.-B., Zhu, Q.-Y., Siew, C.-K.: Extreme learning machine: theory and applications. Neurocomputing 70(1\u20133), 489\u2013501 (2006)","journal-title":"Neurocomputing"},{"key":"57_CR16","series-title":"Lecture Notes in Computer Science","doi-asserted-by":"publisher","first-page":"345","DOI":"10.1007\/978-3-540-31865-1_25","volume-title":"Advances in Information Retrieval","author":"C Goutte","year":"2005","unstructured":"Goutte, C., Gaussier, E.: A probabilistic interpretation of precision, recall and F-score, with implication for evaluation. In: Losada, David E., Fern\u00e1ndez-Luna, Juan M. (eds.) ECIR 2005. LNCS, vol. 3408, pp. 345\u2013359. Springer, Heidelberg (2005). https:\/\/doi.org\/10.1007\/978-3-540-31865-1_25"}],"container-title":["Lecture Notes in Computer Science","Artificial Neural Networks and Machine Learning \u2013 ICANN 2018"],"original-title":[],"link":[{"URL":"http:\/\/link.springer.com\/content\/pdf\/10.1007\/978-3-030-01418-6_57","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2022,9,2]],"date-time":"2022-09-02T19:51:42Z","timestamp":1662148302000},"score":1,"resource":{"primary":{"URL":"http:\/\/link.springer.com\/10.1007\/978-3-030-01418-6_57"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2018]]},"ISBN":["9783030014179","9783030014186"],"references-count":16,"URL":"https:\/\/doi.org\/10.1007\/978-3-030-01418-6_57","relation":{},"ISSN":["0302-9743","1611-3349"],"issn-type":[{"type":"print","value":"0302-9743"},{"type":"electronic","value":"1611-3349"}],"subject":[],"published":{"date-parts":[[2018]]},"assertion":[{"value":"ICANN","order":1,"name":"conference_acronym","label":"Conference Acronym","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"International Conference on Artificial Neural Networks","order":2,"name":"conference_name","label":"Conference Name","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Rhodes","order":3,"name":"conference_city","label":"Conference City","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Greece","order":4,"name":"conference_country","label":"Conference Country","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"2018","order":5,"name":"conference_year","label":"Conference Year","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"4 October 2018","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"7 October 2018","order":8,"name":"conference_end_date","label":"Conference End Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"27","order":9,"name":"conference_number","label":"Conference Number","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"icann2018","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"https:\/\/e-nns.org\/icann2018\/","order":11,"name":"conference_url","label":"Conference URL","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Open","order":1,"name":"type","label":"Type","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information"}},{"value":"easyacademia.org","order":2,"name":"conference_management_system","label":"Conference Management System","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information"}},{"value":"360","order":3,"name":"number_of_submissions_sent_for_review","label":"Number of Submissions Sent for Review","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information"}},{"value":"139","order":4,"name":"number_of_full_papers_accepted","label":"Number of Full Papers Accepted","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information"}},{"value":"28","order":5,"name":"number_of_short_papers_accepted","label":"Number of Short Papers Accepted","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information"}},{"value":"39% - The value is computed by the equation \"Number of Full Papers Accepted \/ Number of Submissions Sent for Review * 100\" and then rounded to a whole number.","order":6,"name":"acceptance_rate_of_full_papers","label":"Acceptance Rate of Full Papers","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information"}},{"value":"2","order":7,"name":"average_number_of_reviews_per_paper","label":"Average Number of Reviews per Paper","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information"}},{"value":"4","order":8,"name":"average_number_of_papers_per_reviewer","label":"Average Number of Papers per Reviewer","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information"}},{"value":"No","order":9,"name":"external_reviewers_involved","label":"External Reviewers Involved","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information"}},{"value":"In addition there are 41 full poster papers and 11 short poster papers included in the proceedings","order":10,"name":"additional_info_on_review_process","label":"Additional Info on Review Process","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information"}}]}}