{"id":"https://openalex.org/W4414054668","doi":"https://doi.org/10.1109/hsi66212.2025.11142397","title":"Probformer: Transformers with Probabilistic Auto-correlation for Acid Dosage Prediction","display_name":"Probformer: Transformers with Probabilistic Auto-correlation for Acid Dosage Prediction","publication_year":2025,"publication_date":"2025-07-16","ids":{"openalex":"https://openalex.org/W4414054668","doi":"https://doi.org/10.1109/hsi66212.2025.11142397"},"language":"en","primary_location":{"id":"doi:10.1109/hsi66212.2025.11142397","is_oa":false,"landing_page_url":"https://doi.org/10.1109/hsi66212.2025.11142397","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2025 17th International Conference on Human System Interaction (HSI)","raw_type":"proceedings-article"},"type":"conference-paper","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/A5100734609","display_name":"Qing Li","orcid":"https://orcid.org/0000-0002-6071-473X"},"institutions":[{"id":"https://openalex.org/I78675632","display_name":"Beijing Information Science & Technology University","ror":"https://ror.org/04xnqep60","country_code":"CN","type":"education","lineage":["https://openalex.org/I78675632"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Qing Li","raw_affiliation_strings":["School of Automation and Electrical Engineering, University of Science and Technology Beijing,Key Laboratory of Knowledge Automation for Industrial Processes, Ministry of Education,Beijing,China,100083"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Automation and Electrical Engineering, University of Science and Technology Beijing,Key Laboratory of Knowledge Automation for Industrial Processes, Ministry of Education,Beijing,China,100083","institution_ids":["https://openalex.org/I78675632"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5044667047","display_name":"Yanyu Yin","orcid":null},"institutions":[{"id":"https://openalex.org/I78675632","display_name":"Beijing Information Science & Technology University","ror":"https://ror.org/04xnqep60","country_code":"CN","type":"education","lineage":["https://openalex.org/I78675632"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yanyu Yin","raw_affiliation_strings":["School of Automation and Electrical Engineering, University of Science and Technology Beijing,Key Laboratory of Knowledge Automation for Industrial Processes, Ministry of Education,Beijing,China,100083"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Automation and Electrical Engineering, University of Science and Technology Beijing,Key Laboratory of Knowledge Automation for Industrial Processes, Ministry of Education,Beijing,China,100083","institution_ids":["https://openalex.org/I78675632"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5103248177","display_name":"Kang-Hyun Jo","orcid":"https://orcid.org/0000-0001-8317-6092"},"institutions":[{"id":"https://openalex.org/I40542001","display_name":"University of Ulsan","ror":"https://ror.org/02c2f8975","country_code":"KR","type":"education","lineage":["https://openalex.org/I40542001"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"Kanghyun Jo","raw_affiliation_strings":["University of Ulsan,Department of Electrical, Electronic and Computer Engineering,South Korea"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Ulsan,Department of Electrical, Electronic and Computer Engineering,South Korea","institution_ids":["https://openalex.org/I40542001"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100618722","display_name":"Li Yuan","orcid":"https://orcid.org/0000-0002-7408-197X"},"institutions":[{"id":"https://openalex.org/I78675632","display_name":"Beijing Information Science & Technology University","ror":"https://ror.org/04xnqep60","country_code":"CN","type":"education","lineage":["https://openalex.org/I78675632"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Li Yuan","raw_affiliation_strings":["School of Automation and Electrical Engineering, University of Science and Technology Beijing,Key Laboratory of Knowledge Automation for Industrial Processes, Ministry of Education,Beijing,China,100083"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Automation and Electrical Engineering, University of Science and Technology Beijing,Key Laboratory of Knowledge Automation for Industrial Processes, Ministry of Education,Beijing,China,100083","institution_ids":["https://openalex.org/I78675632"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"6"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11667","display_name":"Advanced Chemical Sensor Technologies","score":0.9442999958992004,"subfield":{"id":"https://openalex.org/subfields/2204","display_name":"Biomedical 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/T11667","display_name":"Advanced Chemical Sensor Technologies","score":0.9442999958992004,"subfield":{"id":"https://openalex.org/subfields/2204","display_name":"Biomedical 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/probabilistic-logic","display_name":"Probabilistic logic","score":0.5302000045776367},{"id":"https://openalex.org/keywords/froth-flotation","display_name":"Froth flotation","score":0.4968000054359436},{"id":"https://openalex.org/keywords/time-series","display_name":"Time series","score":0.47269999980926514},{"id":"https://openalex.org/keywords/process","display_name":"Process (computing)","score":0.4595000147819519},{"id":"https://openalex.org/keywords/autocorrelation","display_name":"Autocorrelation","score":0.45170000195503235},{"id":"https://openalex.org/keywords/process-control","display_name":"Process control","score":0.38830000162124634},{"id":"https://openalex.org/keywords/series","display_name":"Series (stratigraphy)","score":0.37229999899864197}],"concepts":[{"id":"https://openalex.org/C49937458","wikidata":"https://www.wikidata.org/wiki/Q2599292","display_name":"Probabilistic logic","level":2,"score":0.5302000045776367},{"id":"https://openalex.org/C154366045","wikidata":"https://www.wikidata.org/wiki/Q898459","display_name":"Froth flotation","level":2,"score":0.4968000054359436},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.49459999799728394},{"id":"https://openalex.org/C151406439","wikidata":"https://www.wikidata.org/wiki/Q186588","display_name":"Time series","level":2,"score":0.47269999980926514},{"id":"https://openalex.org/C98045186","wikidata":"https://www.wikidata.org/wiki/Q205663","display_name":"Process (computing)","level":2,"score":0.4595000147819519},{"id":"https://openalex.org/C5297727","wikidata":"https://www.wikidata.org/wiki/Q786970","display_name":"Autocorrelation","level":2,"score":0.45170000195503235},{"id":"https://openalex.org/C155386361","wikidata":"https://www.wikidata.org/wiki/Q1649571","display_name":"Process control","level":3,"score":0.38830000162124634},{"id":"https://openalex.org/C143724316","wikidata":"https://www.wikidata.org/wiki/Q312468","display_name":"Series (stratigraphy)","level":2,"score":0.37229999899864197},{"id":"https://openalex.org/C124681953","wikidata":"https://www.wikidata.org/wiki/Q339062","display_name":"Decomposition","level":2,"score":0.3481999933719635},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.299699991941452},{"id":"https://openalex.org/C21880701","wikidata":"https://www.wikidata.org/wiki/Q2144042","display_name":"Process engineering","level":1,"score":0.28949999809265137},{"id":"https://openalex.org/C114289077","wikidata":"https://www.wikidata.org/wiki/Q3284399","display_name":"Statistical model","level":2,"score":0.2833000123500824},{"id":"https://openalex.org/C184898388","wikidata":"https://www.wikidata.org/wiki/Q1435712","display_name":"Pairwise comparison","level":2,"score":0.2736999988555908},{"id":"https://openalex.org/C148483581","wikidata":"https://www.wikidata.org/wiki/Q446488","display_name":"Feature selection","level":2,"score":0.2685000002384186},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.2615000009536743},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.25929999351501465},{"id":"https://openalex.org/C186060115","wikidata":"https://www.wikidata.org/wiki/Q30336093","display_name":"Biological system","level":1,"score":0.257099986076355},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.25609999895095825},{"id":"https://openalex.org/C66322947","wikidata":"https://www.wikidata.org/wiki/Q11658","display_name":"Transformer","level":3,"score":0.2556999921798706},{"id":"https://openalex.org/C60782215","wikidata":"https://www.wikidata.org/wiki/Q3333679","display_name":"Probabilistic method","level":3,"score":0.25189998745918274}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/hsi66212.2025.11142397","is_oa":false,"landing_page_url":"https://doi.org/10.1109/hsi66212.2025.11142397","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2025 17th International Conference on Human System Interaction (HSI)","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":10,"referenced_works":["https://openalex.org/W1862847311","https://openalex.org/W2013888980","https://openalex.org/W3021773517","https://openalex.org/W3177318507","https://openalex.org/W4385245566","https://openalex.org/W4386912062","https://openalex.org/W4388196580","https://openalex.org/W4389636508","https://openalex.org/W4389671934","https://openalex.org/W4401148116"],"related_works":["https://openalex.org/W4391375266","https://openalex.org/W2899084033","https://openalex.org/W2748952813","https://openalex.org/W2390279801","https://openalex.org/W4391913857","https://openalex.org/W2358668433","https://openalex.org/W4396701345","https://openalex.org/W2376932109","https://openalex.org/W2001405890","https://openalex.org/W4396696052"],"abstract_inverted_index":{"Froth":[0],"flotation":[1,31,52],"is":[2],"a":[3,20,70,87,93],"crucial":[4],"separation":[5],"technique":[6],"in":[7,23,127,147],"the":[8,13,25,46,51,55,80],"metal":[9],"beneficiation":[10],"process.":[11],"Among":[12],"various":[14],"control":[15],"variables,":[16,59],"acid":[17,35,81,148],"dosage":[18,36,82,149],"plays":[19],"significant":[21],"role":[22],"adjusting":[24],"slurry":[26],"pH":[27],"and":[28,54,64,92,103,125,136],"directly":[29],"impacts":[30],"efficiency.":[32],"However,":[33],"traditional":[34],"prediction":[37,75,130,134],"methods":[38],"struggle":[39],"to":[40,45,78,98],"achieve":[41],"accurate":[42],"modeling":[43],"due":[44],"nonlinear,":[47],"time-varying":[48],"nature":[49],"of":[50,129,145],"process":[53,62],"complex":[56],"coupling":[57],"among":[58],"thereby":[60],"hindering":[61],"optimization":[63],"stable":[65],"control.":[66],"This":[67],"study":[68],"proposes":[69],"deep":[71],"learning-based":[72],"time":[73,88],"series":[74,89],"model,":[76],"Probformer,":[77],"address":[79],"forecasting":[83,150],"task.":[84],"Probformer":[85,116,146],"incorporates":[86],"decomposition":[90],"mechanism":[91,97],"probabilistic":[94],"autocorrelation":[95],"attention":[96],"effectively":[99],"capture":[100],"long-term":[101],"trends":[102],"periodic":[104],"variations":[105],"during":[106],"prediction.":[107],"Experiments":[108],"conducted":[109],"on":[110],"real-world":[111],"industrial":[112],"data":[113],"demonstrate":[114],"that":[115],"outperforms":[117],"conventional":[118],"models":[119],"such":[120],"as":[121],"Autoformer,":[122],"Transformer,":[123],"Informer,":[124],"Reformer":[126],"terms":[128],"accuracy,":[131],"achieving":[132],"lower":[133],"errors":[135],"higher":[137],"fitting":[138],"accuracy.":[139],"The":[140],"results":[141],"highlight":[142],"strong":[143],"performance":[144],"for":[151,158],"froth":[152],"flotation,":[153],"indicating":[154],"its":[155],"promising":[156],"potential":[157],"practical":[159],"applications.":[160]},"counts_by_year":[],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2025-10-10T00:00:00"}