{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2024,9,12]],"date-time":"2024-09-12T21:34:48Z","timestamp":1726176888635},"publisher-location":"Cham","reference-count":13,"publisher":"Springer Nature Switzerland","isbn-type":[{"type":"print","value":"9783031180491"},{"type":"electronic","value":"9783031180507"}],"license":[{"start":{"date-parts":[[2022,10,12]],"date-time":"2022-10-12T00:00:00Z","timestamp":1665532800000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springer.com\/tdm"},{"start":{"date-parts":[[2022,10,12]],"date-time":"2022-10-12T00:00:00Z","timestamp":1665532800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.springer.com\/tdm"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2023]]},"DOI":"10.1007\/978-3-031-18050-7_34","type":"book-chapter","created":{"date-parts":[[2022,10,11]],"date-time":"2022-10-11T19:02:55Z","timestamp":1665514975000},"page":"350-360","update-policy":"http:\/\/dx.doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["A Virtual Sensor Approach to\u00a0Estimate the\u00a0Stainless Steel Final Chemical Characterisation"],"prefix":"10.1007","author":[{"ORCID":"http:\/\/orcid.org\/0000-0001-5536-7836","authenticated-orcid":false,"given":"Dami\u00e1n","family":"Nimo","sequence":"first","affiliation":[]},{"ORCID":"http:\/\/orcid.org\/0000-0002-5765-369X","authenticated-orcid":false,"given":"Javier","family":"Gonz\u00e1lez-Enrique","sequence":"additional","affiliation":[]},{"given":"David","family":"Perez","sequence":"additional","affiliation":[]},{"given":"Juan","family":"Almagro","sequence":"additional","affiliation":[]},{"ORCID":"http:\/\/orcid.org\/0000-0003-2662-798X","authenticated-orcid":false,"given":"Daniel","family":"Urda","sequence":"additional","affiliation":[]},{"ORCID":"http:\/\/orcid.org\/0000-0003-4627-0252","authenticated-orcid":false,"given":"Ignacio J.","family":"Turias","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2022,10,12]]},"reference":[{"key":"34_CR1","doi-asserted-by":"crossref","unstructured":"Boser, B.E., Guyon, I.M., Vapnik, V.N.: A training algorithm for optimal margin classifiers. In: Proceedings of the Fifth Annual Workshop on Computational Learning Theory, pp. 144\u2013152 (1992)","DOI":"10.1145\/130385.130401"},{"key":"34_CR2","series-title":"Lecture Notes in Computer Science (Lecture Notes in Artificial Intelligence)","doi-asserted-by":"publisher","first-page":"475","DOI":"10.1007\/978-3-642-01307-2_43","volume-title":"Advances in Knowledge Discovery and Data Mining","author":"C Bunkhumpornpat","year":"2009","unstructured":"Bunkhumpornpat, C., Sinapiromsaran, K., Lursinsap, C.: Safe-Level-SMOTE: Safe-level-synthetic minority over-sampling technique for handling the class imbalanced problem. In: Theeramunkong, T., Kijsirikul, B., Cercone, N., Ho, T.-B. (eds.) PAKDD 2009. LNCS (LNAI), vol. 5476, pp. 475\u2013482. Springer, Heidelberg (2009). https:\/\/doi.org\/10.1007\/978-3-642-01307-2_43"},{"key":"34_CR3","unstructured":"Davis, J.R., et\u00a0al.: Stainless steels. In: ASM International (1994)"},{"key":"34_CR4","doi-asserted-by":"crossref","unstructured":"Dilberoglu, U.M., Gharehpapagh, B., Yaman, U., Dolen, M.: The role of additive manufacturing in the era of industry 4.0. Proc. Manuf. 11, 545\u2013554 (2017)","DOI":"10.1016\/j.promfg.2017.07.148"},{"key":"34_CR5","unstructured":"Dopico, M., G\u00f3mez, A., De\u00a0la Fuente, D., Garc\u00eda, N., Rosillo, R., Puche, J.: A vision of industry 4.0 from an artificial intelligence point of view. In: Proceedings on the International Conference on Artificial Intelligence (ICAI), p. 407. The Steering Committee of The World Congress in Computer Science, Computer (2016)"},{"key":"34_CR6","doi-asserted-by":"crossref","unstructured":"Lee, J., Davari, H., Singh, J., Pandhare, V.: Industrial artificial intelligence for industry 4.0-based manufacturing systems. Manuf. Lett. 18, 20\u201323 (2018)","DOI":"10.1016\/j.mfglet.2018.09.002"},{"issue":"3","key":"34_CR7","doi-asserted-by":"publisher","first-page":"70","DOI":"10.1109\/MSP.2014.2330626","volume":"32","author":"T Li","year":"2015","unstructured":"Li, T., Bolic, M., Djuric, P.M.: Resampling methods for particle filtering: classification, implementation, and strategies. IEEE Signal Process. Mag. 32(3), 70\u201386 (2015)","journal-title":"IEEE Signal Process. Mag."},{"issue":"4\u20136","key":"34_CR8","doi-asserted-by":"publisher","first-page":"39","DOI":"10.1016\/j.mser.2009.03.001","volume":"65","author":"KH Lo","year":"2009","unstructured":"Lo, K.H., Shek, C.H., Lai, J.: Recent developments in stainless steels. Mater. Sci. Eng. R. Rep. 65(4\u20136), 39\u2013104 (2009)","journal-title":"Mater. Sci. Eng. R. Rep."},{"issue":"4","key":"34_CR9","doi-asserted-by":"publisher","first-page":"489","DOI":"10.1016\/j.indmarman.2013.03.001","volume":"42","author":"FJ Mart\u00ednez-L\u00f3pez","year":"2013","unstructured":"Mart\u00ednez-L\u00f3pez, F.J., Casillas, J.: Artificial intelligence-based systems applied in industrial marketing: An historical overview, current and future insights. Ind. Mark. Manage. 42(4), 489\u2013495 (2013)","journal-title":"Ind. Mark. Manage."},{"key":"34_CR10","series-title":"Lecture Notes in Computer Science (Lecture Notes in Artificial Intelligence)","doi-asserted-by":"publisher","first-page":"504","DOI":"10.1007\/978-3-030-29859-3_43","volume-title":"Hybrid Artificial Intelligent Systems","author":"H Mesa","year":"2019","unstructured":"Mesa, H., et al.: A machine learning approach to determine abundance of inclusions in stainless steel. In: P\u00e9rez Garc\u00eda, H., S\u00e1nchez Gonz\u00e1lez, L., Castej\u00f3n Limas, M., Quinti\u00e1n Pardo, H., Corchado Rodr\u00edguez, E. (eds.) HAIS 2019. LNCS (LNAI), vol. 11734, pp. 504\u2013513. Springer, Cham (2019). https:\/\/doi.org\/10.1007\/978-3-030-29859-3_43"},{"issue":"4","key":"34_CR11","doi-asserted-by":"publisher","first-page":"525","DOI":"10.1016\/S0893-6080(05)80056-5","volume":"6","author":"MF M\u00f8ller","year":"1993","unstructured":"M\u00f8ller, M.F.: A scaled conjugate gradient algorithm for fast supervised learning. Neural Netw. 6(4), 525\u2013533 (1993)","journal-title":"Neural Netw."},{"issue":"12","key":"34_CR12","doi-asserted-by":"publisher","first-page":"1565","DOI":"10.1038\/nbt1206-1565","volume":"24","author":"WS Noble","year":"2006","unstructured":"Noble, W.S.: What is a support vector machine? Nat. Biotechnol. 24(12), 1565\u20131567 (2006)","journal-title":"Nat. Biotechnol."},{"issue":"2","key":"34_CR13","doi-asserted-by":"publisher","first-page":"88","DOI":"10.18201\/ijisae.2019252786","volume":"7","author":"MM Saritas","year":"2019","unstructured":"Saritas, M.M., Yasar, A.: Performance analysis of ann and naive bayes classification algorithm for data classification. Int. J. Intell. Syst. Appli. Eng. 7(2), 88\u201391 (2019)","journal-title":"Int. J. Intell. Syst. Appli. Eng."}],"container-title":["Lecture Notes in Networks and Systems","17th International Conference on Soft Computing Models in Industrial and Environmental Applications (SOCO 2022)"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/978-3-031-18050-7_34","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2022,10,11]],"date-time":"2022-10-11T19:06:50Z","timestamp":1665515210000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/978-3-031-18050-7_34"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2022,10,12]]},"ISBN":["9783031180491","9783031180507"],"references-count":13,"URL":"https:\/\/doi.org\/10.1007\/978-3-031-18050-7_34","relation":{},"ISSN":["2367-3370","2367-3389"],"issn-type":[{"type":"print","value":"2367-3370"},{"type":"electronic","value":"2367-3389"}],"subject":[],"published":{"date-parts":[[2022,10,12]]},"assertion":[{"value":"12 October 2022","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}},{"value":"SOCO","order":1,"name":"conference_acronym","label":"Conference Acronym","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"International Workshop on Soft Computing Models in Industrial and Environmental Applications","order":2,"name":"conference_name","label":"Conference Name","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Bilbao","order":3,"name":"conference_city","label":"Conference City","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Spain","order":4,"name":"conference_country","label":"Conference Country","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"2022","order":5,"name":"conference_year","label":"Conference Year","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"5 September 2022","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"7 September 2022","order":8,"name":"conference_end_date","label":"Conference End Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"17","order":9,"name":"conference_number","label":"Conference Number","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"socomoin2022","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"http:\/\/2022.sococonference.eu\/","order":11,"name":"conference_url","label":"Conference URL","group":{"name":"ConferenceInfo","label":"Conference Information"}}]}}