{"id":"https://openalex.org/W4407130398","doi":"https://doi.org/10.1109/ieem62345.2024.10857210","title":"A Comparative Investigation Introducing Regularization Techniques in Linear Regression Models for Quality Prediction in Forming Technology","display_name":"A Comparative Investigation Introducing Regularization Techniques in Linear Regression Models for Quality Prediction in Forming Technology","publication_year":2024,"publication_date":"2024-12-15","ids":{"openalex":"https://openalex.org/W4407130398","doi":"https://doi.org/10.1109/ieem62345.2024.10857210"},"language":"en","primary_location":{"id":"doi:10.1109/ieem62345.2024.10857210","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ieem62345.2024.10857210","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2024 IEEE International Conference on Industrial Engineering and Engineering Management (IEEM)","raw_type":"proceedings-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":false,"oa_status":"closed","oa_url":null,"any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5098686907","display_name":"Alejandra Vicaria","orcid":null},"institutions":[{"id":"https://openalex.org/I62916508","display_name":"Technical University of Munich","ror":"https://ror.org/02kkvpp62","country_code":"DE","type":"education","lineage":["https://openalex.org/I62916508"]},{"id":"https://openalex.org/I4210157642","display_name":"Institute of Automation","ror":"https://ror.org/056qj1t15","country_code":"DE","type":"facility","lineage":["https://openalex.org/I4210157642","https://openalex.org/I78650965"]}],"countries":["DE"],"is_corresponding":true,"raw_author_name":"A. Vicaria","raw_affiliation_strings":["Institute of Automation and Information Systems, Technical University of Munich,Munich,Germany"],"affiliations":[{"raw_affiliation_string":"Institute of Automation and Information Systems, Technical University of Munich,Munich,Germany","institution_ids":["https://openalex.org/I4210157642","https://openalex.org/I62916508"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5071323487","display_name":"Birgit Vogel\u2010Heuser","orcid":"https://orcid.org/0000-0003-2785-8819"},"institutions":[{"id":"https://openalex.org/I4210157642","display_name":"Institute of Automation","ror":"https://ror.org/056qj1t15","country_code":"DE","type":"facility","lineage":["https://openalex.org/I4210157642","https://openalex.org/I78650965"]},{"id":"https://openalex.org/I62916508","display_name":"Technical University of Munich","ror":"https://ror.org/02kkvpp62","country_code":"DE","type":"education","lineage":["https://openalex.org/I62916508"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"B. Vogel-Heuser","raw_affiliation_strings":["Institute of Automation and Information Systems, Technical University of Munich,Munich,Germany"],"affiliations":[{"raw_affiliation_string":"Institute of Automation and Information Systems, Technical University of Munich,Munich,Germany","institution_ids":["https://openalex.org/I4210157642","https://openalex.org/I62916508"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5010757221","display_name":"Marius Kr\u00fcger","orcid":"https://orcid.org/0009-0004-3674-5466"},"institutions":[{"id":"https://openalex.org/I4210157642","display_name":"Institute of Automation","ror":"https://ror.org/056qj1t15","country_code":"DE","type":"facility","lineage":["https://openalex.org/I4210157642","https://openalex.org/I78650965"]},{"id":"https://openalex.org/I62916508","display_name":"Technical University of Munich","ror":"https://ror.org/02kkvpp62","country_code":"DE","type":"education","lineage":["https://openalex.org/I62916508"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"M. Kr\u00fcger","raw_affiliation_strings":["Institute of Automation and Information Systems, Technical University of Munich,Munich,Germany"],"affiliations":[{"raw_affiliation_string":"Institute of Automation and Information Systems, Technical University of Munich,Munich,Germany","institution_ids":["https://openalex.org/I4210157642","https://openalex.org/I62916508"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5079641978","display_name":"Marion Merklein","orcid":"https://orcid.org/0000-0003-0609-7301"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"M. Merklein","raw_affiliation_strings":["Institute of Manufacturing Technology, Friedrich-Alexander-Universit&#x00E4;t,Erlangen-N&#x00FC;rnberg,Germany"],"affiliations":[{"raw_affiliation_string":"Institute of Manufacturing Technology, Friedrich-Alexander-Universit&#x00E4;t,Erlangen-N&#x00FC;rnberg,Germany","institution_ids":[]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5036588940","display_name":"Mathias Lechner","orcid":"https://orcid.org/0000-0002-6117-0076"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"M. Lechner","raw_affiliation_strings":["Institute of Manufacturing Technology, Friedrich-Alexander-Universit&#x00E4;t,Erlangen-N&#x00FC;rnberg,Germany"],"affiliations":[{"raw_affiliation_string":"Institute of Manufacturing Technology, Friedrich-Alexander-Universit&#x00E4;t,Erlangen-N&#x00FC;rnberg,Germany","institution_ids":[]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5098686907"],"corresponding_institution_ids":["https://openalex.org/I4210157642","https://openalex.org/I62916508"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.30040088,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"1230","last_page":"1235"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11201","display_name":"Metallurgy and Material Forming","score":0.9330000281333923,"subfield":{"id":"https://openalex.org/subfields/2211","display_name":"Mechanics of Materials"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T11201","display_name":"Metallurgy and Material Forming","score":0.9330000281333923,"subfield":{"id":"https://openalex.org/subfields/2211","display_name":"Mechanics of Materials"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/regularization","display_name":"Regularization (linguistics)","score":0.6482567191123962},{"id":"https://openalex.org/keywords/linear-regression","display_name":"Linear regression","score":0.5950665473937988},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.4954575300216675},{"id":"https://openalex.org/keywords/proper-linear-model","display_name":"Proper linear model","score":0.4953409731388092},{"id":"https://openalex.org/keywords/regression-analysis","display_name":"Regression analysis","score":0.4727153182029724},{"id":"https://openalex.org/keywords/regression","display_name":"Regression","score":0.4264603853225708},{"id":"https://openalex.org/keywords/applied-mathematics","display_name":"Applied mathematics","score":0.3631260097026825},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.35829561948776245},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.35371309518814087},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.34940481185913086},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.3260385990142822},{"id":"https://openalex.org/keywords/bayesian-multivariate-linear-regression","display_name":"Bayesian multivariate linear regression","score":0.29014497995376587}],"concepts":[{"id":"https://openalex.org/C2776135515","wikidata":"https://www.wikidata.org/wiki/Q17143721","display_name":"Regularization (linguistics)","level":2,"score":0.6482567191123962},{"id":"https://openalex.org/C48921125","wikidata":"https://www.wikidata.org/wiki/Q10861030","display_name":"Linear regression","level":2,"score":0.5950665473937988},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.4954575300216675},{"id":"https://openalex.org/C32224588","wikidata":"https://www.wikidata.org/wiki/Q7250175","display_name":"Proper linear model","level":4,"score":0.4953409731388092},{"id":"https://openalex.org/C152877465","wikidata":"https://www.wikidata.org/wiki/Q208042","display_name":"Regression analysis","level":2,"score":0.4727153182029724},{"id":"https://openalex.org/C83546350","wikidata":"https://www.wikidata.org/wiki/Q1139051","display_name":"Regression","level":2,"score":0.4264603853225708},{"id":"https://openalex.org/C28826006","wikidata":"https://www.wikidata.org/wiki/Q33521","display_name":"Applied mathematics","level":1,"score":0.3631260097026825},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.35829561948776245},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.35371309518814087},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.34940481185913086},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3260385990142822},{"id":"https://openalex.org/C64946054","wikidata":"https://www.wikidata.org/wiki/Q4874476","display_name":"Bayesian multivariate linear regression","level":3,"score":0.29014497995376587}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/ieem62345.2024.10857210","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ieem62345.2024.10857210","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2024 IEEE International Conference on Industrial Engineering and Engineering Management (IEEM)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":11,"referenced_works":["https://openalex.org/W1965168076","https://openalex.org/W2035466733","https://openalex.org/W2526280165","https://openalex.org/W2600746833","https://openalex.org/W2768277063","https://openalex.org/W4290039714","https://openalex.org/W4296626148","https://openalex.org/W4304142077","https://openalex.org/W4384789235","https://openalex.org/W4387135325","https://openalex.org/W4390242499"],"related_works":["https://openalex.org/W1519288722","https://openalex.org/W31220157","https://openalex.org/W2379898021","https://openalex.org/W267133670","https://openalex.org/W2376794814","https://openalex.org/W3216594821","https://openalex.org/W1915333409","https://openalex.org/W4226066678","https://openalex.org/W4399767649","https://openalex.org/W2288557197"],"abstract_inverted_index":{"In":[0],"this":[1],"investigation,":[2],"linear":[3],"models":[4],"used":[5],"for":[6,34,40],"quality":[7,42,117],"prediction":[8,43],"of":[9,45,89,118],"a":[10,20],"final":[11,79],"product":[12],"are":[13,48,93],"compared":[14],"and":[15,55,74,87,101,111],"evaluated":[16,69],"using":[17,77],"data":[18],"from":[19],"real":[21],"manufacturing":[22],"process":[23,104],"in":[24,60,97,114],"forming":[25],"technology":[26],"(i.e.,":[27],"flexible":[28],"rolling":[29],"process).":[30],"Two":[31],"alternative":[32],"methods":[33],"simplifying":[35],"the":[36,41,61,78,85,90,98,115,119],"feature":[37,102],"selection":[38,103],"method":[39,66,92],"model":[44,72],"manufactured":[46,120],"blanks":[47],"presented.":[49],"This":[50],"work":[51],"proposes":[52],"implementing":[53],"L1":[54],"$\\mathbf{L}":[56],"2$":[57],"regularization":[58],"techniques":[59],"original":[62],"regression":[63],"model.":[64],"The":[65],"is":[67,105],"then":[68],"based":[70],"on":[71],"complexity":[73],"performance":[75],"metrics":[76],"predictions.":[80],"By":[81],"comparing":[82],"these":[83],"indicators,":[84],"effectiveness":[86],"benefits":[88],"proposed":[91],"confirmed.":[94],"A":[95],"simplification":[96],"model-building":[99],"effort":[100],"developed":[106],"while":[107],"providing":[108],"an":[109],"efficient":[110],"comparable":[112],"accuracy":[113],"predicted":[116],"blanks.":[121]},"counts_by_year":[],"updated_date":"2025-12-23T23:11:35.936235","created_date":"2025-10-10T00:00:00"}
