{"id":"https://openalex.org/W4405804294","doi":"https://doi.org/10.1007/s10489-024-05922-z","title":"A Physically-Constrained Ensemble Learning Rate of Penetration Prediction Model based on Multi-Source Data Fusion","display_name":"A Physically-Constrained Ensemble Learning Rate of Penetration Prediction Model based on Multi-Source Data Fusion","publication_year":2024,"publication_date":"2024-12-26","ids":{"openalex":"https://openalex.org/W4405804294","doi":"https://doi.org/10.1007/s10489-024-05922-z"},"language":"en","primary_location":{"id":"doi:10.1007/s10489-024-05922-z","is_oa":false,"landing_page_url":"https://doi.org/10.1007/s10489-024-05922-z","pdf_url":null,"source":{"id":"https://openalex.org/S74726891","display_name":"Applied Intelligence","issn_l":"0924-669X","issn":["0924-669X","1573-7497"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319900","host_organization_name":"Springer Science+Business Media","host_organization_lineage":["https://openalex.org/P4310319900","https://openalex.org/P4310319965"],"host_organization_lineage_names":["Springer Science+Business Media","Springer Nature"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Applied Intelligence","raw_type":"journal-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/A5064469029","display_name":"Yongdong Fan","orcid":"https://orcid.org/0000-0001-6908-1142"},"institutions":[{"id":"https://openalex.org/I204553293","display_name":"China University of Petroleum, Beijing","ror":"https://ror.org/041qf4r12","country_code":"CN","type":"education","lineage":["https://openalex.org/I204553293"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Yongdong Fan","raw_affiliation_strings":["College of Artificial Intelligence, China University of Petroleum, Beijing, 102249, China","State Key Laboratory of Petroleum Resources and Prospecting, China University of Petroleum, Beijing, 102249, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"College of Artificial Intelligence, China University of Petroleum, Beijing, 102249, China","institution_ids":["https://openalex.org/I204553293"]},{"raw_affiliation_string":"State Key Laboratory of Petroleum Resources and Prospecting, China University of Petroleum, Beijing, 102249, China","institution_ids":["https://openalex.org/I204553293"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Yan Jin","orcid":null},"institutions":[{"id":"https://openalex.org/I204553293","display_name":"China University of Petroleum, Beijing","ror":"https://ror.org/041qf4r12","country_code":"CN","type":"education","lineage":["https://openalex.org/I204553293"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Yan Jin","raw_affiliation_strings":["College of Artificial Intelligence, China University of Petroleum, Beijing, 102249, China","State Key Laboratory of Petroleum Resources and Prospecting, China University of Petroleum, Beijing, 102249, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"College of Artificial Intelligence, China University of Petroleum, Beijing, 102249, China","institution_ids":["https://openalex.org/I204553293"]},{"raw_affiliation_string":"State Key Laboratory of Petroleum Resources and Prospecting, China University of Petroleum, Beijing, 102249, China","institution_ids":["https://openalex.org/I204553293"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5046249637","display_name":"Huiwen Pang","orcid":"https://orcid.org/0000-0003-3000-8102"},"institutions":[{"id":"https://openalex.org/I204553293","display_name":"China University of Petroleum, Beijing","ror":"https://ror.org/041qf4r12","country_code":"CN","type":"education","lineage":["https://openalex.org/I204553293"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Huiwen Pang","raw_affiliation_strings":["College of Science, China University of Petroleum, Beijing, 102249, China","State Key Laboratory of Petroleum Resources and Prospecting, China University of Petroleum, Beijing, 102249, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"College of Science, China University of Petroleum, Beijing, 102249, China","institution_ids":["https://openalex.org/I204553293"]},{"raw_affiliation_string":"State Key Laboratory of Petroleum Resources and Prospecting, China University of Petroleum, Beijing, 102249, China","institution_ids":["https://openalex.org/I204553293"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5101509803","display_name":"Yunhu Lu","orcid":"https://orcid.org/0000-0003-0278-5203"},"institutions":[{"id":"https://openalex.org/I204553293","display_name":"China University of Petroleum, Beijing","ror":"https://ror.org/041qf4r12","country_code":"CN","type":"education","lineage":["https://openalex.org/I204553293"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yunhu Lu","raw_affiliation_strings":["State Key Laboratory of Petroleum Resources and Prospecting, China University of Petroleum, Beijing, 102249, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"State Key Laboratory of Petroleum Resources and Prospecting, China University of Petroleum, Beijing, 102249, China","institution_ids":["https://openalex.org/I204553293"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":["https://openalex.org/A5064469029"],"corresponding_institution_ids":["https://openalex.org/I204553293"],"apc_list":{"value":3090,"currency":"USD","value_usd":3090},"apc_paid":null,"fwci":0.5879,"has_fulltext":false,"cited_by_count":3,"citation_normalized_percentile":{"value":0.63681852,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":97,"max":98},"biblio":{"volume":"55","issue":"3","first_page":null,"last_page":null},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10892","display_name":"Drilling and Well Engineering","score":0.9998999834060669,"subfield":{"id":"https://openalex.org/subfields/2212","display_name":"Ocean Engineering"},"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/T10892","display_name":"Drilling and Well Engineering","score":0.9998999834060669,"subfield":{"id":"https://openalex.org/subfields/2212","display_name":"Ocean Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10635","display_name":"Hydraulic Fracturing and Reservoir Analysis","score":0.9991999864578247,"subfield":{"id":"https://openalex.org/subfields/2210","display_name":"Mechanical Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T13050","display_name":"Oil and Gas Production Techniques","score":0.9932000041007996,"subfield":{"id":"https://openalex.org/subfields/2212","display_name":"Ocean Engineering"},"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/computer-science","display_name":"Computer science","score":0.7963166236877441},{"id":"https://openalex.org/keywords/random-forest","display_name":"Random forest","score":0.6876865029335022},{"id":"https://openalex.org/keywords/interpretability","display_name":"Interpretability","score":0.6487741470336914},{"id":"https://openalex.org/keywords/support-vector-machine","display_name":"Support vector machine","score":0.5877635478973389},{"id":"https://openalex.org/keywords/mean-absolute-percentage-error","display_name":"Mean absolute percentage error","score":0.5545873045921326},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.5355185270309448},{"id":"https://openalex.org/keywords/predictive-modelling","display_name":"Predictive modelling","score":0.5142192840576172},{"id":"https://openalex.org/keywords/decision-tree","display_name":"Decision tree","score":0.49264246225357056},{"id":"https://openalex.org/keywords/regression","display_name":"Regression","score":0.4466441571712494},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.42543458938598633},{"id":"https://openalex.org/keywords/ensemble-learning","display_name":"Ensemble learning","score":0.42039161920547485},{"id":"https://openalex.org/keywords/boosting","display_name":"Boosting (machine learning)","score":0.41243910789489746},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.38561344146728516},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.3610091805458069},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.18886715173721313},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.09601610898971558}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7963166236877441},{"id":"https://openalex.org/C169258074","wikidata":"https://www.wikidata.org/wiki/Q245748","display_name":"Random forest","level":2,"score":0.6876865029335022},{"id":"https://openalex.org/C2781067378","wikidata":"https://www.wikidata.org/wiki/Q17027399","display_name":"Interpretability","level":2,"score":0.6487741470336914},{"id":"https://openalex.org/C12267149","wikidata":"https://www.wikidata.org/wiki/Q282453","display_name":"Support vector machine","level":2,"score":0.5877635478973389},{"id":"https://openalex.org/C150217764","wikidata":"https://www.wikidata.org/wiki/Q6803607","display_name":"Mean absolute percentage error","level":3,"score":0.5545873045921326},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.5355185270309448},{"id":"https://openalex.org/C45804977","wikidata":"https://www.wikidata.org/wiki/Q7239673","display_name":"Predictive modelling","level":2,"score":0.5142192840576172},{"id":"https://openalex.org/C84525736","wikidata":"https://www.wikidata.org/wiki/Q831366","display_name":"Decision tree","level":2,"score":0.49264246225357056},{"id":"https://openalex.org/C83546350","wikidata":"https://www.wikidata.org/wiki/Q1139051","display_name":"Regression","level":2,"score":0.4466441571712494},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.42543458938598633},{"id":"https://openalex.org/C45942800","wikidata":"https://www.wikidata.org/wiki/Q245652","display_name":"Ensemble learning","level":2,"score":0.42039161920547485},{"id":"https://openalex.org/C46686674","wikidata":"https://www.wikidata.org/wiki/Q466303","display_name":"Boosting (machine learning)","level":2,"score":0.41243910789489746},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.38561344146728516},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.3610091805458069},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.18886715173721313},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.09601610898971558}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1007/s10489-024-05922-z","is_oa":false,"landing_page_url":"https://doi.org/10.1007/s10489-024-05922-z","pdf_url":null,"source":{"id":"https://openalex.org/S74726891","display_name":"Applied Intelligence","issn_l":"0924-669X","issn":["0924-669X","1573-7497"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319900","host_organization_name":"Springer Science+Business Media","host_organization_lineage":["https://openalex.org/P4310319900","https://openalex.org/P4310319965"],"host_organization_lineage_names":["Springer Science+Business Media","Springer Nature"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Applied Intelligence","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":32,"referenced_works":["https://openalex.org/W1968376774","https://openalex.org/W2013345849","https://openalex.org/W2021098490","https://openalex.org/W2024324964","https://openalex.org/W2082381131","https://openalex.org/W2760335212","https://openalex.org/W2942140875","https://openalex.org/W2946517338","https://openalex.org/W2975906708","https://openalex.org/W3008508208","https://openalex.org/W3094117609","https://openalex.org/W3096718018","https://openalex.org/W3109737138","https://openalex.org/W3130689994","https://openalex.org/W3170876782","https://openalex.org/W3187732917","https://openalex.org/W4200030976","https://openalex.org/W4200285150","https://openalex.org/W4296821790","https://openalex.org/W4313469902","https://openalex.org/W4380569373","https://openalex.org/W4381620743","https://openalex.org/W4385246560","https://openalex.org/W4385613035","https://openalex.org/W4385702953","https://openalex.org/W4387629694","https://openalex.org/W4387962327","https://openalex.org/W4388284120","https://openalex.org/W4394975909","https://openalex.org/W4396532229","https://openalex.org/W4399589714","https://openalex.org/W4401711174"],"related_works":["https://openalex.org/W2905156999","https://openalex.org/W4229460275","https://openalex.org/W4296079469","https://openalex.org/W1987518466","https://openalex.org/W3135046080","https://openalex.org/W3023033471","https://openalex.org/W2014852328","https://openalex.org/W2809161969","https://openalex.org/W3175454233","https://openalex.org/W4394010018"],"abstract_inverted_index":null,"counts_by_year":[{"year":2026,"cited_by_count":3}],"updated_date":"2026-08-30T07:30:35.949966","created_date":"2025-10-10T00:00:00"}