{"id":"https://openalex.org/W4396897482","doi":"https://doi.org/10.62411/jimat.v1i1.10502","title":"Ensemble Learning Model in Predicting Corrosion Inhibition Capability of Pyridazine Compounds","display_name":"Ensemble Learning Model in Predicting Corrosion Inhibition Capability of Pyridazine Compounds","publication_year":2024,"publication_date":"2024-04-29","ids":{"openalex":"https://openalex.org/W4396897482","doi":"https://doi.org/10.62411/jimat.v1i1.10502"},"language":"en","primary_location":{"id":"doi:10.62411/jimat.v1i1.10502","doi":"https://doi.org/10.62411/jimat.v1i1.10502","is_oa":true,"landing_page_url":"http://dx.doi.org/10.62411/jimat.v1i1.10502","pdf_url":"https://publikasi.dinus.ac.id/jimat/article/download/10502/4581","source":{"id":"https://openalex.org/S4404669339","display_name":"Journal of Multiscale Materials Informatics","issn_l":"3047-5724","issn":["3047-5724"],"is_oa":false,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":"https://openalex.org/P4310315221","host_organization_name":"Nuswantoro Dian University","host_organization_lineage":["https://openalex.org/P4310315221"],"host_organization_lineage_names":["Nuswantoro Dian University"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Journal of Multiscale Materials Informatics","raw_type":"journal-article"},"volume":null,"type":"article","is_traditional":true,"indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"hybrid","oa_url":"https://publikasi.dinus.ac.id/jimat/article/download/10502/4581","any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5010001135","display_name":"Dian Arif Rachman","orcid":null,"observed_orcids":[]},"institutions":[{"id":"https://openalex.org/I4210140882","display_name":"Institut Teknologi dan Sains Nahdlatul Ulama","ror":"https://ror.org/040egw157","country_code":"ID","type":"education","lineage":["https://openalex.org/I4210140882"]}],"countries":["ID"],"is_corresponding":false,"raw_author_name":"Dian Arif Rachman","raw_affiliation_strings":["Institut Teknologi dan Sains Nahdlatul Ulama Pekalongan"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Institut Teknologi dan Sains Nahdlatul Ulama Pekalongan","institution_ids":["https://openalex.org/I4210140882"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5039933141","display_name":"Muhamad Akrom","orcid":"https://orcid.org/0000-0003-3249-110X","observed_orcids":["https://orcid.org/0000-0003-3249-110X"]},"institutions":[{"id":"https://openalex.org/I4210127958","display_name":"Universitas Dian Nuswantoro","ror":"https://ror.org/02csxcg02","country_code":"ID","type":"education","lineage":["https://openalex.org/I4210127958"]}],"countries":["ID"],"is_corresponding":false,"raw_author_name":"Muhamad Akrom","raw_affiliation_strings":["Universitas Dian Nuswantoro"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Universitas Dian Nuswantoro","institution_ids":["https://openalex.org/I4210127958"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.2624,"has_fulltext":true,"cited_by_count":3,"citation_normalized_percentile":{"value":0.32293735,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":91,"max":95},"biblio":{"volume":"1","issue":"1","first_page":"38","last_page":"43"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11948","display_name":"Machine Learning in Materials Science","score":0.4587000012397766,"subfield":{"id":"https://openalex.org/subfields/2505","display_name":"Materials Chemistry"},"field":{"id":"https://openalex.org/fields/25","display_name":"Materials Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T11948","display_name":"Machine Learning in Materials Science","score":0.4587000012397766,"subfield":{"id":"https://openalex.org/subfields/2505","display_name":"Materials Chemistry"},"field":{"id":"https://openalex.org/fields/25","display_name":"Materials Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10310","display_name":"Corrosion Behavior and Inhibition","score":0.36250001192092896,"subfield":{"id":"https://openalex.org/subfields/2505","display_name":"Materials Chemistry"},"field":{"id":"https://openalex.org/fields/25","display_name":"Materials Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10211","display_name":"Computational Drug Discovery Methods","score":0.16429999470710754,"subfield":{"id":"https://openalex.org/subfields/3002","display_name":"Drug Discovery"},"field":{"id":"https://openalex.org/fields/30","display_name":"Pharmacology, Toxicology and Pharmaceutics"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/corrosion-inhibition","display_name":"corrosion inhibition","score":0.843999981880188},{"id":"https://openalex.org/keywords/corrosion-inhibition-efficiency","display_name":"corrosion inhibition efficiency","score":0.722000002861023},{"id":"https://openalex.org/keywords/quantitative-structure-property-relationship","display_name":"QSPR","score":0.6980000138282776},{"id":"https://openalex.org/keywords/ensemble-learning","display_name":"ensemble learning","score":0.8970000147819519},{"id":"https://openalex.org/keywords/gradient-boosting-regression","display_name":"gradient boosting regression","score":0.9120000004768372},{"id":"https://openalex.org/keywords/iron-corrosion","display_name":"iron corrosion","score":0.5640000104904175},{"id":"https://openalex.org/keywords/metal-corrosion-inhibitors","display_name":"metal corrosion inhibitors","score":0.5070000290870667},{"id":"https://openalex.org/keywords/qsar-prediction","display_name":"QSAR prediction","score":0.6129999756813049}],"concepts":[{"id":"https://openalex.org/C2777355660","wikidata":"https://www.wikidata.org/wiki/Q420238","display_name":"Pyridazine","level":2,"score":0.8840024471282959},{"id":"https://openalex.org/C45942800","wikidata":"https://www.wikidata.org/wiki/Q245652","display_name":"Ensemble learning","level":2,"score":0.6063789129257202},{"id":"https://openalex.org/C20625102","wikidata":"https://www.wikidata.org/wiki/Q137056","display_name":"Corrosion","level":2,"score":0.5285709500312805},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.49756768345832825},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.3725823163986206},{"id":"https://openalex.org/C185592680","wikidata":"https://www.wikidata.org/wiki/Q2329","display_name":"Chemistry","level":0,"score":0.3105977773666382},{"id":"https://openalex.org/C192562407","wikidata":"https://www.wikidata.org/wiki/Q228736","display_name":"Materials science","level":0,"score":0.28408700227737427},{"id":"https://openalex.org/C191897082","wikidata":"https://www.wikidata.org/wiki/Q11467","display_name":"Metallurgy","level":1,"score":0.09770813584327698},{"id":"https://openalex.org/C71240020","wikidata":"https://www.wikidata.org/wiki/Q186011","display_name":"Stereochemistry","level":1,"score":0.07331991195678711}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.62411/jimat.v1i1.10502","doi":"https://doi.org/10.62411/jimat.v1i1.10502","is_oa":true,"landing_page_url":"http://dx.doi.org/10.62411/jimat.v1i1.10502","pdf_url":"https://publikasi.dinus.ac.id/jimat/article/download/10502/4581","source":{"id":"https://openalex.org/S4404669339","display_name":"Journal of Multiscale Materials Informatics","issn_l":"3047-5724","issn":["3047-5724"],"is_oa":false,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":"https://openalex.org/P4310315221","host_organization_name":"Nuswantoro Dian University","host_organization_lineage":["https://openalex.org/P4310315221"],"host_organization_lineage_names":["Nuswantoro Dian University"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Journal of Multiscale Materials Informatics","raw_type":"journal-article"}],"best_oa_location":{"id":"doi:10.62411/jimat.v1i1.10502","doi":"https://doi.org/10.62411/jimat.v1i1.10502","is_oa":true,"landing_page_url":"http://dx.doi.org/10.62411/jimat.v1i1.10502","pdf_url":"https://publikasi.dinus.ac.id/jimat/article/download/10502/4581","source":{"id":"https://openalex.org/S4404669339","display_name":"Journal of Multiscale Materials Informatics","issn_l":"3047-5724","issn":["3047-5724"],"is_oa":false,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":"https://openalex.org/P4310315221","host_organization_name":"Nuswantoro Dian University","host_organization_lineage":["https://openalex.org/P4310315221"],"host_organization_lineage_names":["Nuswantoro Dian University"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Journal of Multiscale Materials Informatics","raw_type":"journal-article"},"sustainable_development_goals":[],"study_designs":[],"awards":[],"funders":[],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4396897482.pdf","grobid_xml":"https://content.openalex.org/works/W4396897482.grobid-xml"},"referenced_works_count":29,"referenced_works":["https://openalex.org/W3005526147","https://openalex.org/W3049269637","https://openalex.org/W3153663858","https://openalex.org/W4205174124","https://openalex.org/W4207086083","https://openalex.org/W4210558868","https://openalex.org/W4213133243","https://openalex.org/W4213162425","https://openalex.org/W4220882267","https://openalex.org/W4225294356","https://openalex.org/W4288710390","https://openalex.org/W4293365963","https://openalex.org/W4304943032","https://openalex.org/W4313463359","https://openalex.org/W4315572963","https://openalex.org/W4379883432","https://openalex.org/W4383069355","https://openalex.org/W4386401776","https://openalex.org/W4386812946","https://openalex.org/W4386826036","https://openalex.org/W4388191819","https://openalex.org/W4390232769","https://openalex.org/W4391997375","https://openalex.org/W4392651919","https://openalex.org/W4392657935","https://openalex.org/W4393237873","https://openalex.org/W4394566571","https://openalex.org/W4394807710","https://openalex.org/W4394858327"],"related_works":["https://openalex.org/W4390232769","https://openalex.org/W4383069355","https://openalex.org/W4402740954","https://openalex.org/W4396897261","https://openalex.org/W4405028194","https://openalex.org/W4396897474","https://openalex.org/W4404012611","https://openalex.org/W4392657935","https://openalex.org/W4396897194","https://openalex.org/W4386401776"],"abstract_inverted_index":{"Empirical":[0],"studies":[1],"of":[2,10,36,75,113],"possible":[3],"compound":[4],"corrosion":[5,37,109],"inhibitors":[6],"require":[7],"a":[8,18,83],"lot":[9],"money,":[11],"time,":[12],"and":[13,73,118],"resources.":[14],"Therefore,":[15],"we":[16],"used":[17],"machine":[19,89],"learning":[20,90],"(ML)":[21],"paradigm":[22],"based":[23],"on":[24,86,110],"quantitative":[25],"structure-property":[26],"relationship":[27],"(QSPR)":[28],"models":[29],"to":[30,96,107],"evaluate":[31],"ensemble":[32],"algorithms":[33,91],"as":[34,101,116],"predictors":[35],"inhibition":[38],"efficiency":[39],"(CIE)":[40],"values.":[41],"Our":[42],"investigation":[43],"reveals":[44],"that":[45,103],"the":[46,62,105,111],"gradient":[47],"boosting":[48],"(GB)":[49],"regressor":[50],"model":[51],"outperforms":[52],"other":[53],"ensemble-based":[54],"models.":[55],"This":[56],"advantage":[57],"is":[58],"evaluated":[59],"objectively":[60],"using":[61],"metrics":[63],"root":[64],"mean":[65,69],"square":[66],"error":[67,71],"(RMSE),":[68],"absolute":[70],"(MAE),":[72],"coefficient":[74],"determination":[76],"(R2).":[77],"In":[78],"summary,":[79],"our":[80],"research":[81],"provides":[82],"new":[84],"perspective":[85],"how":[87],"well":[88],"in":[92],"particular":[93],"ensembles":[94],"work":[95],"identify":[97],"organic":[98],"molecules":[99],"such":[100,115],"pyridazine":[102],"have":[104],"potential":[106],"prevent":[108],"surfaces":[112],"metals":[114],"iron":[117],"its":[119],"alloys.":[120]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":2}],"updated_date":"2026-10-06T10:28:23.643775","created_date":"2024-05-15T00:00:00"}
