{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,3,26]],"date-time":"2025-03-26T22:32:01Z","timestamp":1743028321254,"version":"3.40.3"},"publisher-location":"Cham","reference-count":20,"publisher":"Springer International Publishing","isbn-type":[{"type":"print","value":"9783030687793"},{"type":"electronic","value":"9783030687809"}],"license":[{"start":{"date-parts":[[2021,1,1]],"date-time":"2021-01-01T00:00:00Z","timestamp":1609459200000},"content-version":"tdm","delay-in-days":0,"URL":"http:\/\/www.springer.com\/tdm"},{"start":{"date-parts":[[2021,1,1]],"date-time":"2021-01-01T00:00:00Z","timestamp":1609459200000},"content-version":"vor","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":[[2021]]},"DOI":"10.1007\/978-3-030-68780-9_3","type":"book-chapter","created":{"date-parts":[[2021,2,24]],"date-time":"2021-02-24T17:04:13Z","timestamp":1614186253000},"page":"26-33","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["Environmental Time Series Prediction with Missing Data by Machine Learning and Dynamics Recostruction"],"prefix":"10.1007","author":[{"given":"Francesco","family":"Camastra","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Vincenzo","family":"Capone","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Angelo","family":"Ciaramella","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Tony Christian","family":"Landi","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Angelo","family":"Riccio","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Antonino","family":"Staiano","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2021,2,25]]},"reference":[{"key":"3_CR1","doi-asserted-by":"publisher","first-page":"54","DOI":"10.1016\/j.ecoinf.2018.12.001","volume":"49","author":"E Chianese","year":"2019","unstructured":"Chianese, E., Camastra, F., Ciaramella, A., Landi, T., Staiano, A., Riccio, A.: Spatio-temporal learning in predicting ambient particulate matter concentration by multi-layer perceptron. Ecol. Inf. 49, 54\u201361 (2019)","journal-title":"Ecol. Inf."},{"key":"3_CR2","doi-asserted-by":"publisher","first-page":"620","DOI":"10.1109\/78.489035","volume":"44","author":"D Hirshberg","year":"1996","unstructured":"Hirshberg, D., Merhav, N.: Robust methods for model order estimation. IEEE Trans. Signal Process. 44, 620\u2013628 (1996)","journal-title":"IEEE Trans. Signal Process."},{"key":"3_CR3","volume-title":"Pattern Classification","author":"R Duda","year":"2001","unstructured":"Duda, R., Hart, P., Stork, D.: Pattern Classification. Wiley, New York (2001)"},{"key":"3_CR4","doi-asserted-by":"publisher","unstructured":"The Elements of Statistical Learning. SSS. Springer, New York (2009). https:\/\/doi.org\/10.1007\/978-0-387-84858-7_9","DOI":"10.1007\/978-0-387-84858-7_9"},{"key":"3_CR5","doi-asserted-by":"publisher","first-page":"1021","DOI":"10.1007\/s00521-009-0266-y","volume":"18","author":"F Camastra","year":"2009","unstructured":"Camastra, F., Filippone, M.: A comparative evaluation of nonlinear dynamics methods for time series prediction. Neural Comput. Appl. 18, 1021\u20131029 (2009)","journal-title":"Neural Comput. Appl."},{"key":"3_CR6","series-title":"Lecture Notes in Mathematics","doi-asserted-by":"publisher","first-page":"230","DOI":"10.1007\/BFb0091916","volume-title":"Dynamical Systems and Turbulence, Warwick 1980","author":"R Ma\u00f1\u00e9","year":"1981","unstructured":"Ma\u00f1\u00e9, R.: On the dimension of the compact invariant sets of certain non-linear maps. In: Rand, D., Young, L.-S. (eds.) Dynamical Systems and Turbulence, Warwick 1980. LNM, vol. 898, pp. 230\u2013242. Springer, Heidelberg (1981). https:\/\/doi.org\/10.1007\/BFb0091916"},{"key":"3_CR7","doi-asserted-by":"crossref","unstructured":"Takens, F.: Detecting strange attractor in turbolence. In: Dynamical Systems and Turbolence, Warwick, pp. 366\u2013381. MIT Press (1981)","DOI":"10.1007\/BFb0091924"},{"key":"3_CR8","doi-asserted-by":"publisher","first-page":"26","DOI":"10.1016\/j.ins.2015.08.029","volume":"328","author":"F Camastra","year":"2016","unstructured":"Camastra, F., Staiano, A.: Intrinsic dimension estimation: advances and open problems. Inf. Sci. 328, 26\u201341 (2016)","journal-title":"Inf. Sci."},{"key":"3_CR9","doi-asserted-by":"publisher","first-page":"189","DOI":"10.1016\/0167-2789(83)90298-1","volume":"9","author":"P Grassberger","year":"1983","unstructured":"Grassberger, P., Procaccia, I.: Measuring the strangeness of strange attractors. Physica D 9, 189\u2013208 (1983)","journal-title":"Physica D"},{"key":"3_CR10","doi-asserted-by":"publisher","first-page":"1005","DOI":"10.1007\/s00521-016-2616-x","volume":"26","author":"F Camastra","year":"2018","unstructured":"Camastra, F., Esposito, F., Staiano, A.: Linear SVM-based recognition of elementary juggling movements using correlation dimension of Euler angles of a single arm. Neural Comput. Appl. 26, 1005\u20131013 (2018)","journal-title":"Neural Comput. Appl."},{"key":"3_CR11","volume-title":"Introductory Techniques for 3-D Computer Vision","author":"E Trucco","year":"1998","unstructured":"Trucco, E., Verri, A.: Introductory Techniques for 3-D Computer Vision. Prentice Hall, Englewood Cliffs (1998)"},{"key":"3_CR12","volume-title":"Statistical Learning Theory","author":"V Vapnik","year":"1998","unstructured":"Vapnik, V.: Statistical Learning Theory. Wiley, New York (1998)"},{"key":"3_CR13","volume-title":"An Introduction to Support Vector Machines","author":"N Cristianini","year":"2000","unstructured":"Cristianini, N., Shawe-Taylor, J.: An Introduction to Support Vector Machines. Cambridge University Press, Cambridge (2000)"},{"key":"3_CR14","volume-title":"Learning with Kernels","author":"B Sch\u00f6lkopf","year":"2002","unstructured":"Sch\u00f6lkopf, B., Smola, A.: Learning with Kernels. MIT Press, Cambridge (2002)"},{"key":"3_CR15","unstructured":"Joachim, T.: Making large-scale SVM learning practical. In: Advances in Kernel Methods-Support Vector Learning, pp. 169\u2013184. MIT Press (1999)"},{"key":"3_CR16","doi-asserted-by":"publisher","DOI":"10.4135\/9781412985079","volume-title":"Missing Data","author":"P Allison","year":"2002","unstructured":"Allison, P.: Missing Data. Sage Publications, Thousand Oaks (2002)"},{"issue":"1","key":"3_CR17","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1111\/j.2517-6161.1977.tb01600.x","volume":"39","author":"A Dempster","year":"1977","unstructured":"Dempster, A., Laird, N., Rubin, D.: Maximum likelihood from incomplete data via the EM algorithm. J. R. Stat. Soc. 39(1), 1\u201338 (1977)","journal-title":"J. R. Stat. Soc."},{"key":"3_CR18","doi-asserted-by":"publisher","first-page":"311","DOI":"10.1086\/296465","volume":"62","author":"J Scheinkman","year":"1989","unstructured":"Scheinkman, J., Le Baron, B.: Nonlinear dynamics and stock returns. J. Bus. 62, 311\u2013337 (1989)","journal-title":"J. Bus."},{"key":"3_CR19","volume-title":"Gaussian Processes for Machine Learning","author":"C Williams","year":"2006","unstructured":"Williams, C., Rasmussen, C.: Gaussian Processes for Machine Learning. MIT Press, Cambridge (2006)"},{"key":"3_CR20","doi-asserted-by":"crossref","unstructured":"Camastra, F., Vinciarelli, A.: Markovian models for sequential data. In: Advanced Information and Knowledge Processing, pp. 294\u2013340. MIT Press (2015)","DOI":"10.1007\/978-1-4471-6735-8_10"}],"container-title":["Lecture Notes in Computer Science","Pattern Recognition. ICPR International Workshops and Challenges"],"original-title":[],"language":"en","link":[{"URL":"http:\/\/link.springer.com\/content\/pdf\/10.1007\/978-3-030-68780-9_3","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,8,24]],"date-time":"2024-08-24T20:10:14Z","timestamp":1724530214000},"score":1,"resource":{"primary":{"URL":"http:\/\/link.springer.com\/10.1007\/978-3-030-68780-9_3"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2021]]},"ISBN":["9783030687793","9783030687809"],"references-count":20,"URL":"https:\/\/doi.org\/10.1007\/978-3-030-68780-9_3","relation":{},"ISSN":["0302-9743","1611-3349"],"issn-type":[{"type":"print","value":"0302-9743"},{"type":"electronic","value":"1611-3349"}],"subject":[],"published":{"date-parts":[[2021]]},"assertion":[{"value":"25 February 2021","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}},{"value":"ICPR","order":1,"name":"conference_acronym","label":"Conference Acronym","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"International Conference on Pattern Recognition","order":2,"name":"conference_name","label":"Conference Name","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"2021","order":5,"name":"conference_year","label":"Conference Year","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"10 January 2021","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"11 January 2021","order":8,"name":"conference_end_date","label":"Conference End Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"ICPR2020","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"http:\/\/www.icpr2020.it\/","order":11,"name":"conference_url","label":"Conference URL","group":{"name":"ConferenceInfo","label":"Conference Information"}}]}}