{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,2,14]],"date-time":"2026-02-14T20:57:35Z","timestamp":1771102655929,"version":"3.50.1"},"publisher-location":"Cham","reference-count":25,"publisher":"Springer International Publishing","isbn-type":[{"value":"9783030206550","type":"print"},{"value":"9783030206567","type":"electronic"}],"license":[{"start":{"date-parts":[[2019,1,1]],"date-time":"2019-01-01T00:00:00Z","timestamp":1546300800000},"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":[[2019]]},"DOI":"10.1007\/978-3-030-20656-7_10","type":"book-chapter","created":{"date-parts":[[2019,6,4]],"date-time":"2019-06-04T19:02:40Z","timestamp":1559674960000},"page":"186-205","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":4,"title":["MaLTESE: Large-Scale Simulation-Driven Machine Learning for Transient Driving Cycles"],"prefix":"10.1007","author":[{"given":"Shashi M.","family":"Aithal","sequence":"first","affiliation":[]},{"given":"Prasanna","family":"Balaprakash","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2019,5,17]]},"reference":[{"key":"10_CR1","unstructured":"Abadi, M., et al.: Tensorflow: a system for large-scale machine learning. In: OSDI, vol. 16, pp. 265\u2013283 (2016)"},{"issue":"2","key":"10_CR2","doi-asserted-by":"publisher","first-page":"336","DOI":"10.1080\/00102202.2012.718297","volume":"185","author":"SM Aithal","year":"2013","unstructured":"Aithal, S.M.: Analysis of the current signature in a constant-volume combustion chamber. Combust. Sci. Technol. 185(2), 336\u2013349 (2013). \n                      https:\/\/doi.org\/10.1080\/00102202.2012.718297","journal-title":"Combust. Sci. Technol."},{"issue":"8","key":"10_CR3","doi-asserted-by":"publisher","first-page":"1184","DOI":"10.1080\/00102202.2013.781593","volume":"185","author":"SM Aithal","year":"2013","unstructured":"Aithal, S.M.: Prediction of voltage signature in a homogeneous charge compression ignition (HCCI) engine fueled with propane and acetylene. Combust. Sci. Technol. 185(8), 1184\u20131201 (2013). \n                      https:\/\/doi.org\/10.1080\/00102202.2013.781593","journal-title":"Combust. Sci. Technol."},{"key":"10_CR4","doi-asserted-by":"crossref","unstructured":"Aithal, S.M.: Development of an integrated design tool for real-time analyses of performance and emissions in engines powered by alternative fuels. In: Proceedings of SAE 11th International Conference on Engines & Vehicles. SAE (2013)","DOI":"10.4271\/2013-24-0134"},{"key":"10_CR5","series-title":"Lecture Notes in Computer Science","doi-asserted-by":"publisher","first-page":"87","DOI":"10.1007\/978-3-319-20119-1_7","volume-title":"High Performance Computing","author":"SM Aithal","year":"2015","unstructured":"Aithal, S.M., Wild, S.M.: ACCOLADES: a scalable workflow framework for large-scale simulation and analyses of automotive engines. In: Kunkel, J.M., Ludwig, T. (eds.) ISC High Performance 2015. LNCS, vol. 9137, pp. 87\u201395. Springer, Cham (2015). \n                      https:\/\/doi.org\/10.1007\/978-3-319-20119-1_7"},{"key":"10_CR6","doi-asserted-by":"publisher","DOI":"10.1007\/978-1-4615-7566-5","volume-title":"Pattern Recognition and Machine Learning","author":"CM Bishop","year":"2006","unstructured":"Bishop, C.M.: Pattern Recognition and Machine Learning, vol. 1. Springer, New York (2006). \n                      https:\/\/doi.org\/10.1007\/978-1-4615-7566-5"},{"issue":"2","key":"10_CR7","first-page":"123","volume":"24","author":"L Breiman","year":"1996","unstructured":"Breiman, L.: Bagging predictors. Mach. Learn. 24(2), 123\u2013140 (1996)","journal-title":"Mach. Learn."},{"issue":"1","key":"10_CR8","doi-asserted-by":"publisher","first-page":"5","DOI":"10.1023\/A:1010933404324","volume":"45","author":"L Breiman","year":"2001","unstructured":"Breiman, L.: Random forests. Mach. Learn. 45(1), 5\u201332 (2001)","journal-title":"Mach. Learn."},{"key":"10_CR9","doi-asserted-by":"crossref","unstructured":"Chen, T., Guestrin, C.: Xgboost: a scalable tree boosting system. arXiv preprint \n                      arXiv:1603.02754\n                      \n                     (2016)","DOI":"10.1145\/2939672.2939785"},{"key":"10_CR10","unstructured":"Chollet, F., et al.: Keras (2015). \n                      https:\/\/keras.io"},{"key":"10_CR11","unstructured":"Drucker, H.: Improving regressors using boosting techniques. In: ICML, vol. 97, pp. 107\u2013115 (1997)"},{"issue":"4","key":"10_CR12","doi-asserted-by":"publisher","first-page":"367","DOI":"10.1016\/S0167-9473(01)00065-2","volume":"38","author":"JH Friedman","year":"2002","unstructured":"Friedman, J.H.: Stochastic gradient boosting. Comput. Stat. Data Anal. 38(4), 367\u2013378 (2002)","journal-title":"Comput. Stat. Data Anal."},{"issue":"1","key":"10_CR13","doi-asserted-by":"publisher","first-page":"3","DOI":"10.1007\/s10994-006-6226-1","volume":"63","author":"P Geurts","year":"2006","unstructured":"Geurts, P., Ernst, D., Wehenkel, L.: Extremely randomized trees. Mach. Learn. 63(1), 3\u201342 (2006)","journal-title":"Mach. Learn."},{"key":"10_CR14","volume-title":"Deep Learning","author":"I Goodfellow","year":"2016","unstructured":"Goodfellow, I., Bengio, Y., Courville, A., Bengio, Y.: Deep Learning, vol. 1. MIT press, Cambridge (2016)"},{"issue":"4","key":"10_CR15","doi-asserted-by":"publisher","first-page":"321","DOI":"10.1243\/14680874JER00807","volume":"8","author":"N Hashemi","year":"2007","unstructured":"Hashemi, N., Clark, N.: Artificial neural network as a predictive tool for emissions from heavy-duty diesel vehicles in Southern California. Int. J. Eng. Res. 8(4), 321\u2013336 (2007)","journal-title":"Int. J. Eng. Res."},{"issue":"1","key":"10_CR16","doi-asserted-by":"publisher","first-page":"55","DOI":"10.1080\/00401706.1970.10488634","volume":"12","author":"AE Hoerl","year":"1970","unstructured":"Hoerl, A.E., Kennard, R.W.: Ridge regression: biased estimation for nonorthogonal problems. Technometrics 12(1), 55\u201367 (1970)","journal-title":"Technometrics"},{"issue":"7","key":"10_CR17","first-page":"601","volume":"22","author":"HC Krijnsen","year":"1999","unstructured":"Krijnsen, H.C., van Kooten, W.E., Calis, H.P.A., Verbeek, R.P., Bleek, C.M.: Prediction of NOx emissions from a transiently operating diesel engine using an artificial neural network. Chem. Eng. Technol. Industr. Chem. Plant Equip. Process Eng. Biotechnol. 22(7), 601\u2013607 (1999)","journal-title":"Chem. Eng. Technol. Industr. Chem. Plant Equip. Process Eng. Biotechnol."},{"issue":"7553","key":"10_CR18","doi-asserted-by":"publisher","first-page":"436","DOI":"10.1038\/nature14539","volume":"521","author":"Y LeCun","year":"2015","unstructured":"LeCun, Y., Bengio, Y., Hinton, G.: Deep learning. Nature 521(7553), 436\u2013444 (2015)","journal-title":"Nature"},{"issue":"1","key":"10_CR19","doi-asserted-by":"publisher","first-page":"14","DOI":"10.1002\/widm.8","volume":"1","author":"WY Loh","year":"2011","unstructured":"Loh, W.Y.: Classification and regression trees. Wiley Interdisc. Rev. Data Min. Knowl. Discov. 1(1), 14\u201323 (2011)","journal-title":"Wiley Interdisc. Rev. Data Min. Knowl. Discov."},{"key":"10_CR20","series-title":"Lecture Notes in Computer Science (Lecture Notes in Artificial Intelligence)","doi-asserted-by":"publisher","first-page":"346","DOI":"10.1007\/978-3-642-33460-3_28","volume-title":"Machine Learning and Knowledge Discovery in Databases","author":"G Louppe","year":"2012","unstructured":"Louppe, G., Geurts, P.: Ensembles on random patches. In: Flach, P.A., De Bie, T., Cristianini, N. (eds.) ECML PKDD 2012. LNCS (LNAI), vol. 7523, pp. 346\u2013361. Springer, Heidelberg (2012). \n                      https:\/\/doi.org\/10.1007\/978-3-642-33460-3_28"},{"issue":"2","key":"10_CR21","doi-asserted-by":"publisher","first-page":"239","DOI":"10.1080\/00401706.1979.10489755","volume":"21","author":"M. D. McKay","year":"1979","unstructured":"McKay, M., Beckman, R., Conover, W.: Comparison the three methods for selecting values of input variable in the analysis of output from a computer code. Technometrics; (United States). \n                      https:\/\/doi.org\/10.1080\/00401706.1979.10489755","journal-title":"Technometrics"},{"issue":"8\u20139","key":"10_CR22","doi-asserted-by":"publisher","first-page":"824","DOI":"10.1016\/j.applthermaleng.2005.10.006","volume":"26","author":"A Parlak","year":"2006","unstructured":"Parlak, A., Islamoglu, Y., Yasar, H., Egrisogut, A.: Application of artificial neural network to predict specific fuel consumption and exhaust temperature for a diesel engine. Appl. Therm. Eng. 26(8\u20139), 824\u2013828 (2006)","journal-title":"Appl. Therm. Eng."},{"key":"10_CR23","first-page":"2825","volume":"12","author":"F Pedregosa","year":"2011","unstructured":"Pedregosa, F., et al.: Scikit-learn: machine learning in Python. J. Mach. Learn. Res. 12, 2825\u20132830 (2011)","journal-title":"J. Mach. Learn. Res."},{"issue":"3","key":"10_CR24","doi-asserted-by":"publisher","first-page":"707","DOI":"10.1007\/s11831-017-9212-9","volume":"25","author":"N Shrivastava","year":"2018","unstructured":"Shrivastava, N., Khan, Z.M.: Application of soft computing in the field of internal combustion engines: a review. Arch. Comput. Meth. Eng. 25(3), 707\u2013726 (2018)","journal-title":"Arch. Comput. Meth. Eng."},{"issue":"3","key":"10_CR25","doi-asserted-by":"publisher","first-page":"199","DOI":"10.1023\/B:STCO.0000035301.49549.88","volume":"14","author":"AJ Smola","year":"2004","unstructured":"Smola, A.J., Sch\u00f6lkopf, B.: A tutorial on support vector regression. Stat. Comput. 14(3), 199\u2013222 (2004)","journal-title":"Stat. Comput."}],"container-title":["Lecture Notes in Computer Science","High Performance Computing"],"original-title":[],"language":"en","link":[{"URL":"http:\/\/link.springer.com\/content\/pdf\/10.1007\/978-3-030-20656-7_10","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2019,6,4]],"date-time":"2019-06-04T19:18:29Z","timestamp":1559675909000},"score":1,"resource":{"primary":{"URL":"http:\/\/link.springer.com\/10.1007\/978-3-030-20656-7_10"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2019]]},"ISBN":["9783030206550","9783030206567"],"references-count":25,"URL":"https:\/\/doi.org\/10.1007\/978-3-030-20656-7_10","relation":{},"ISSN":["0302-9743","1611-3349"],"issn-type":[{"value":"0302-9743","type":"print"},{"value":"1611-3349","type":"electronic"}],"subject":[],"published":{"date-parts":[[2019]]},"assertion":[{"value":"17 May 2019","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}},{"value":"ISC High Performance","order":1,"name":"conference_acronym","label":"Conference Acronym","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"International Conference on High Performance Computing","order":2,"name":"conference_name","label":"Conference Name","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Frankfurt","order":3,"name":"conference_city","label":"Conference City","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Germany","order":4,"name":"conference_country","label":"Conference Country","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"2019","order":5,"name":"conference_year","label":"Conference Year","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"16 June 2019","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"20 June 2019","order":8,"name":"conference_end_date","label":"Conference End Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"34","order":9,"name":"conference_number","label":"Conference Number","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"supercomputing2019","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"https:\/\/www.isc-hpc.com\/","order":11,"name":"conference_url","label":"Conference URL","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Double-blind","order":1,"name":"type","label":"Type","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information"}},{"value":"Linklings","order":2,"name":"conference_management_system","label":"Conference Management System","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information"}},{"value":"70","order":3,"name":"number_of_submissions_sent_for_review","label":"Number of Submissions Sent for Review","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information"}},{"value":"17","order":4,"name":"number_of_full_papers_accepted","label":"Number of Full Papers Accepted","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information"}},{"value":"0","order":5,"name":"number_of_short_papers_accepted","label":"Number of Short Papers Accepted","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information"}},{"value":"24% - 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":"4-5","order":7,"name":"average_number_of_reviews_per_paper","label":"Average Number of Reviews per Paper","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information"}},{"value":"n\/a","order":8,"name":"average_number_of_papers_per_reviewer","label":"Average Number of Papers per Reviewer","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information"}},{"value":"Yes","order":9,"name":"external_reviewers_involved","label":"External Reviewers Involved","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information"}}]}}