{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2024,9,5]],"date-time":"2024-09-05T17:31:00Z","timestamp":1725557460264},"publisher-location":"Berlin, Heidelberg","reference-count":14,"publisher":"Springer Berlin Heidelberg","isbn-type":[{"type":"print","value":"9783642138027"},{"type":"electronic","value":"9783642138034"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2010]]},"DOI":"10.1007\/978-3-642-13803-4_38","type":"book-chapter","created":{"date-parts":[[2010,6,11]],"date-time":"2010-06-11T11:11:36Z","timestamp":1276254696000},"page":"304-311","source":"Crossref","is-referenced-by-count":0,"title":["Support Vector Regression Algorithms in the Forecasting of Daily Maximums of Tropospheric Ozone Concentration in Madrid"],"prefix":"10.1007","author":[{"given":"E. G.","family":"Ortiz-Garc\u00eda","sequence":"first","affiliation":[]},{"given":"S.","family":"Salcedo-Sanz","sequence":"additional","affiliation":[]},{"given":"A. M.","family":"P\u00e9rez-Bellido","sequence":"additional","affiliation":[]},{"given":"J.","family":"Gasc\u00f3n-Moreno","sequence":"additional","affiliation":[]},{"given":"A.","family":"Portilla-Figueras","sequence":"additional","affiliation":[]}],"member":"297","reference":[{"issue":"1-2","key":"38_CR1","doi-asserted-by":"publisher","first-page":"179","DOI":"10.1016\/S0169-7439(98)00063-X","volume":"42","author":"B. Massart","year":"1998","unstructured":"Massart, B., Kvalheim, O.M.: Ozone forecasting from meteorological variables: Part I. Predictive models by moving window and partial least squares regression. Chemometrics and Intelligent Laboratory Systems\u00a042(1-2), 179\u2013190 (1998)","journal-title":"Chemometrics and Intelligent Laboratory Systems"},{"issue":"1-2","key":"38_CR2","doi-asserted-by":"publisher","first-page":"191","DOI":"10.1016\/S0169-7439(98)00064-1","volume":"42","author":"B. Massart","year":"1998","unstructured":"Massart, B., Kvalheim, O.M.: Ozone forecasting from meteorological variables: Part II. Daily maximum ground-level ozone concentration from local weather forecasts. Chemometrics and Intelligent Laboratory Systems\u00a042(1-2), 191\u2013197 (1998)","journal-title":"Chemometrics and Intelligent Laboratory Systems"},{"issue":"1","key":"38_CR3","first-page":"2","volume":"49","author":"M. Garfias-V\u00e1zquez","year":"2005","unstructured":"Garfias-V\u00e1zquez, M., Audry-S\u00e1nchez, J., Garfias-Ayala, F.J.: Tropospheric ozone prediction in Mexico city. Journal of the Mexican Chemistry Society\u00a049(1), 2\u20139 (2005)","journal-title":"Journal of the Mexican Chemistry Society"},{"key":"38_CR4","doi-asserted-by":"publisher","first-page":"2967","DOI":"10.1016\/j.atmosenv.2006.12.013","volume":"41","author":"U. Brunelli","year":"2007","unstructured":"Brunelli, U., Piazza, V., Pignato, L., Sorbello, F., Vitabile, S.: Two-days ahead prediction of daily maximum concentrations of SO\n                2, O\n                3, PM\n                10, NO\n                2, CO in the urban area of Palermo, Italy. Atmospheric Environment\u00a041, 2967\u20132995 (2007)","journal-title":"Atmospheric Environment"},{"key":"38_CR5","doi-asserted-by":"publisher","first-page":"332","DOI":"10.1016\/j.ecolmodel.2006.05.031","volume":"198","author":"D. Wang","year":"2006","unstructured":"Wang, D., Lu, W.: Ground-level ozone prediction using multilayer perceptron trained with an innovative hybrid approach. Ecological Modelling\u00a0198, 332\u2013340 (2006)","journal-title":"Ecological Modelling"},{"issue":"4-6","key":"38_CR6","doi-asserted-by":"publisher","first-page":"550","DOI":"10.1016\/j.neucom.2007.07.020","volume":"71","author":"W. Wang","year":"2008","unstructured":"Wang, W., Men, C., Lu, W.: Online prediction model based on support vector machine. Neurocomputing\u00a071(4-6), 550\u2013558 (2008)","journal-title":"Neurocomputing"},{"key":"38_CR7","doi-asserted-by":"publisher","first-page":"109","DOI":"10.1016\/j.scitotenv.2008.01.035","volume":"395","author":"W. Lu","year":"2008","unstructured":"Lu, W., Wang, D.: Ground-level ozone prediction by support vector machine approach with a cost-sensitive classification scheme. Science of the Total Environment\u00a0395, 109\u2013116 (2008)","journal-title":"Science of the Total Environment"},{"issue":"6","key":"38_CR8","doi-asserted-by":"publisher","first-page":"939","DOI":"10.1016\/j.renene.2003.11.009","volume":"29","author":"M.A. Mohandes","year":"2004","unstructured":"Mohandes, M.A., Halawani, T.O., Rehman, S., Hussain, A.A.: Support vector machines for wind speed prediction. Renewable Energy\u00a029(6), 939\u2013947 (2004)","journal-title":"Renewable Energy"},{"issue":"1-2","key":"38_CR9","doi-asserted-by":"publisher","first-page":"101","DOI":"10.1016\/j.aca.2004.12.085","volume":"537","author":"F. Luan","year":"2005","unstructured":"Luan, F., Xue, C., Zhang, R., Zhao, C., Liu, M., Hu, Z., Fan, B.: Prediction of retention time of a variety of volatile organic compounds based on the heuristic method and support vector machine. Analytica Chimica Acta\u00a0537(1-2), 101\u2013110 (2005)","journal-title":"Analytica Chimica Acta"},{"issue":"5","key":"38_CR10","doi-asserted-by":"publisher","first-page":"693","DOI":"10.1016\/j.chemosphere.2004.10.032","volume":"59","author":"W.-Z. Lu","year":"2005","unstructured":"Lu, W.-Z., Wang, W.-J.: Potential assessment of the support vector machine method in forecasting ambient air pollutant trends. Chemosphere\u00a059(5), 693\u2013701 (2005)","journal-title":"Chemosphere"},{"issue":"6","key":"38_CR11","doi-asserted-by":"publisher","first-page":"745","DOI":"10.1016\/j.engappai.2006.10.008","volume":"20","author":"S. Osowski","year":"2007","unstructured":"Osowski, S., Garanty, K.: Forecasting of the daily meteorological pollution using wavelets and support vector machine. Engineering Applications of Artificial Intelligence\u00a020(6), 745\u2013755 (2007)","journal-title":"Engineering Applications of Artificial Intelligence"},{"key":"38_CR12","doi-asserted-by":"publisher","first-page":"3683","DOI":"10.1016\/j.neucom.2009.07.009","volume":"72","author":"E. Ortiz-Garc\u00eda","year":"2009","unstructured":"Ortiz-Garc\u00eda, E., Salcedo-Sanz, S., P\u00e9rez-Bellido, A., Portilla-Figueras, J.A.: Improving the training time of support vector regression algorithms through novel hyper-parameters search space reductions. Neurocomputing\u00a072, 3683\u20133691 (2009)","journal-title":"Neurocomputing"},{"key":"38_CR13","unstructured":"Smola, A.J., Schlkopf, B.: A tutorial on support vector regression. Statistics and Computing (1998)"},{"key":"38_CR14","doi-asserted-by":"publisher","first-page":"7561","DOI":"10.1016\/j.atmosenv.2008.05.057","volume":"42","author":"G. Hoek","year":"2008","unstructured":"Hoek, G., Beelen, R., de Hoogh, K., Vienneau, D., Gulliver, J., Fischer, P., Briggs, D.: A review of land-use regression models to assess spatial variation of outdoor air pollution. Atmospheric Environment\u00a042, 7561\u20137578 (2008)","journal-title":"Atmospheric Environment"}],"container-title":["Lecture Notes in Computer Science","Hybrid Artificial Intelligence Systems"],"original-title":[],"link":[{"URL":"http:\/\/link.springer.com\/content\/pdf\/10.1007\/978-3-642-13803-4_38.pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2021,4,30]],"date-time":"2021-04-30T12:13:23Z","timestamp":1619784803000},"score":1,"resource":{"primary":{"URL":"http:\/\/link.springer.com\/10.1007\/978-3-642-13803-4_38"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2010]]},"ISBN":["9783642138027","9783642138034"],"references-count":14,"URL":"https:\/\/doi.org\/10.1007\/978-3-642-13803-4_38","relation":{},"ISSN":["0302-9743","1611-3349"],"issn-type":[{"type":"print","value":"0302-9743"},{"type":"electronic","value":"1611-3349"}],"subject":[],"published":{"date-parts":[[2010]]}}}