{"id":"https://openalex.org/W7135198941","doi":"https://doi.org/10.1109/iccp68926.2025.11427134","title":"Predicting Lap Times in Formula 1: A Deep Learning Approach Using LSTM Networks","display_name":"Predicting Lap Times in Formula 1: A Deep Learning Approach Using LSTM Networks","publication_year":2025,"publication_date":"2025-10-16","ids":{"openalex":"https://openalex.org/W7135198941","doi":"https://doi.org/10.1109/iccp68926.2025.11427134"},"language":null,"primary_location":{"id":"doi:10.1109/iccp68926.2025.11427134","is_oa":false,"landing_page_url":"https://doi.org/10.1109/iccp68926.2025.11427134","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2025 IEEE 21st International Conference on Intelligent Computer Communication and Processing (ICCP)","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/A5043485325","display_name":"MA Kara","orcid":"https://orcid.org/0000-0001-9092-8598"},"institutions":[{"id":"https://openalex.org/I51826884","display_name":"Kocaeli \u00dcniversitesi","ror":"https://ror.org/0411seq30","country_code":"TR","type":"education","lineage":["https://openalex.org/I51826884"]}],"countries":["TR"],"is_corresponding":true,"raw_author_name":"Muhammed Faruk Kara","raw_affiliation_strings":["Kocaeli University,Electronics and Communication Engineering,Kocaeli,Turkey"],"affiliations":[{"raw_affiliation_string":"Kocaeli University,Electronics and Communication Engineering,Kocaeli,Turkey","institution_ids":["https://openalex.org/I51826884"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5128638723","display_name":"Ayhan K\u00fc\u00e7\u00fckman\u0130sa","orcid":null},"institutions":[{"id":"https://openalex.org/I51826884","display_name":"Kocaeli \u00dcniversitesi","ror":"https://ror.org/0411seq30","country_code":"TR","type":"education","lineage":["https://openalex.org/I51826884"]}],"countries":["TR"],"is_corresponding":false,"raw_author_name":"Ayhan K\u00fc\u00e7\u00fckmanisa","raw_affiliation_strings":["Kocaeli University,Electronics and Communication Engineering,Kocaeli,Turkey"],"affiliations":[{"raw_affiliation_string":"Kocaeli University,Electronics and Communication Engineering,Kocaeli,Turkey","institution_ids":["https://openalex.org/I51826884"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5043485325"],"corresponding_institution_ids":["https://openalex.org/I51826884"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.8833307,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"5"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T13702","display_name":"Machine Learning in Healthcare","score":0.08839999884366989,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T13702","display_name":"Machine Learning in Healthcare","score":0.08839999884366989,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T11273","display_name":"Advanced Graph Neural Networks","score":0.05480000004172325,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10028","display_name":"Topic Modeling","score":0.053300000727176666,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.7250000238418579},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.4212999939918518},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.3538999855518341},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.3343999981880188},{"id":"https://openalex.org/keywords/deep-neural-networks","display_name":"Deep neural networks","score":0.3034999966621399}],"concepts":[{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7332000136375427},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.7250000238418579},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.559499979019165},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.4212999939918518},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.3538999855518341},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.3343999981880188},{"id":"https://openalex.org/C2984842247","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep neural networks","level":3,"score":0.3034999966621399},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.30149999260902405},{"id":"https://openalex.org/C2781067378","wikidata":"https://www.wikidata.org/wiki/Q17027399","display_name":"Interpretability","level":2,"score":0.2897000014781952},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.26030001044273376},{"id":"https://openalex.org/C26517878","wikidata":"https://www.wikidata.org/wiki/Q228039","display_name":"Key (lock)","level":2,"score":0.2542000114917755}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/iccp68926.2025.11427134","is_oa":false,"landing_page_url":"https://doi.org/10.1109/iccp68926.2025.11427134","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2025 IEEE 21st International Conference on Intelligent Computer Communication and Processing (ICCP)","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":9,"referenced_works":["https://openalex.org/W2164686139","https://openalex.org/W2581983145","https://openalex.org/W2754051771","https://openalex.org/W2971724044","https://openalex.org/W3196402958","https://openalex.org/W4321504591","https://openalex.org/W4391384264","https://openalex.org/W4406230979","https://openalex.org/W4409637932"],"related_works":[],"abstract_inverted_index":{"One":[0],"of":[1,57],"the":[2,13,20,53,72,78,127],"most":[3],"critical":[4],"factors":[5],"influencing":[6],"success":[7],"in":[8],"Formula":[9],"1":[10],"racing":[11],"is":[12,67,89],"ability":[14],"to":[15,34,99,115],"make":[16],"strategic":[17,152],"decisions":[18],"at":[19],"optimal":[21],"moment.":[22],"These":[23],"decisions\u2014such":[24],"as":[25],"pit":[26],"stop":[27],"timing":[28],"and":[29,75,85,96,111,118,137,150],"tire":[30],"selection\u2014are":[31],"deeply":[32],"tied":[33],"lap":[35,55,120],"time":[36,48,56,121],"dynamics.":[37],"In":[38],"this":[39],"study,":[40],"we":[41],"propose":[42],"a":[43,58,130],"Long":[44],"Short-Term":[45],"Memory":[46],"(LSTM)-based":[47],"series":[49],"model":[50,66,128],"for":[51,133],"predicting":[52],"next":[54],"driver":[59,95],"using":[60],"real-world":[61],"multidimensional":[62],"race":[63,135,147],"data.":[64],"The":[65,103],"trained":[68],"on":[69,77],"data":[70,83],"from":[71],"2021\u20132023":[73],"seasons":[74],"evaluated":[76],"2024":[79],"season.":[80],"A":[81],"comprehensive":[82],"preprocessing":[84],"feature":[86],"engineering":[87],"pipeline":[88],"introduced,":[90],"integrating":[91],"race-specific":[92],"variables":[93],"with":[94],"team":[97],"characteristics":[98],"enhance":[100],"predictive":[101,125],"performance.":[102],"proposed":[104],"architecture":[105],"effectively":[106],"captures":[107],"both":[108],"sequential":[109],"dependencies":[110],"contextual":[112],"information,":[113],"leading":[114],"more":[116],"accurate":[117],"realistic":[119],"forecasts.":[122],"Beyond":[123],"its":[124],"capability,":[126],"offers":[129],"promising":[131],"foundation":[132],"real-time":[134],"assistants":[136],"decision-support":[138],"systems.":[139,154],"Future":[140],"enhancements":[141],"may":[142],"include":[143],"driver-personalized":[144],"architectures,":[145],"dynamic":[146],"condition":[148],"modeling,":[149],"integrated":[151],"recommendation":[153]},"counts_by_year":[],"updated_date":"2026-03-15T07:15:06.534987","created_date":"2026-03-14T00:00:00"}
