{"id":"https://openalex.org/W4406619498","doi":"https://doi.org/10.1145/3704814.3706585","title":"Subway station escalator data prediction based on MA-Transformer","display_name":"Subway station escalator data prediction based on MA-Transformer","publication_year":2024,"publication_date":"2024-11-28","ids":{"openalex":"https://openalex.org/W4406619498","doi":"https://doi.org/10.1145/3704814.3706585"},"language":"en","primary_location":{"id":"doi:10.1145/3704814.3706585","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3704814.3706585","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 8th International Conference on Computer Science and Application Engineering","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/A5115949780","display_name":"Yang Fei","orcid":null},"institutions":[{"id":"https://openalex.org/I4210118629","display_name":"NARI Group (China)","ror":"https://ror.org/02egn3136","country_code":"CN","type":"facility","lineage":["https://openalex.org/I4210118629"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Yang Fei","raw_affiliation_strings":["Nanjing Nanrui Industrial Control Technology Co., Ltd., Nanjing, Jiangsu, China"],"raw_orcid":"https://orcid.org/0009-0008-1281-9730","affiliations":[{"raw_affiliation_string":"Nanjing Nanrui Industrial Control Technology Co., Ltd., Nanjing, Jiangsu, China","institution_ids":["https://openalex.org/I4210118629"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5102772286","display_name":"Ziqi Wang","orcid":"https://orcid.org/0009-0001-5722-6495"},"institutions":[{"id":"https://openalex.org/I4210118629","display_name":"NARI Group (China)","ror":"https://ror.org/02egn3136","country_code":"CN","type":"facility","lineage":["https://openalex.org/I4210118629"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Ziqi Wang","raw_affiliation_strings":["Nanjing Nanrui Industrial Control Technology Co., Ltd., Nanjing, Jiangsu, China"],"raw_orcid":"https://orcid.org/0009-0001-5722-6495","affiliations":[{"raw_affiliation_string":"Nanjing Nanrui Industrial Control Technology Co., Ltd., Nanjing, Jiangsu, China","institution_ids":["https://openalex.org/I4210118629"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5112922858","display_name":"H. Li","orcid":"https://orcid.org/0009-0004-8090-652X"},"institutions":[{"id":"https://openalex.org/I4210118629","display_name":"NARI Group (China)","ror":"https://ror.org/02egn3136","country_code":"CN","type":"facility","lineage":["https://openalex.org/I4210118629"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Huaxuan Li","raw_affiliation_strings":["Nanjing Nanrui Industrial Control Technology Co., Ltd., Nanjing, Jiangsu, China"],"raw_orcid":"https://orcid.org/0009-0004-8090-652X","affiliations":[{"raw_affiliation_string":"Nanjing Nanrui Industrial Control Technology Co., Ltd., Nanjing, Jiangsu, China","institution_ids":["https://openalex.org/I4210118629"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5115949780"],"corresponding_institution_ids":["https://openalex.org/I4210118629"],"apc_list":null,"apc_paid":null,"fwci":0.876,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":{"value":0.85840148,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":96,"max":98},"biblio":{"volume":null,"issue":null,"first_page":"140","last_page":"148"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T13955","display_name":"Evaluation Methods in Various Fields","score":0.9922999739646912,"subfield":{"id":"https://openalex.org/subfields/2302","display_name":"Ecological Modeling"},"field":{"id":"https://openalex.org/fields/23","display_name":"Environmental Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T13955","display_name":"Evaluation Methods in Various Fields","score":0.9922999739646912,"subfield":{"id":"https://openalex.org/subfields/2302","display_name":"Ecological Modeling"},"field":{"id":"https://openalex.org/fields/23","display_name":"Environmental Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T14011","display_name":"Elevator Systems and Control","score":0.9890999794006348,"subfield":{"id":"https://openalex.org/subfields/2207","display_name":"Control and Systems 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/T13832","display_name":"Advanced Decision-Making Techniques","score":0.9803000092506409,"subfield":{"id":"https://openalex.org/subfields/1710","display_name":"Information Systems"},"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/computer-science","display_name":"Computer science","score":0.5928901433944702},{"id":"https://openalex.org/keywords/transformer","display_name":"Transformer","score":0.47820067405700684},{"id":"https://openalex.org/keywords/electrical-engineering","display_name":"Electrical engineering","score":0.2264593541622162},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.21126484870910645},{"id":"https://openalex.org/keywords/voltage","display_name":"Voltage","score":0.074128657579422}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5928901433944702},{"id":"https://openalex.org/C66322947","wikidata":"https://www.wikidata.org/wiki/Q11658","display_name":"Transformer","level":3,"score":0.47820067405700684},{"id":"https://openalex.org/C119599485","wikidata":"https://www.wikidata.org/wiki/Q43035","display_name":"Electrical engineering","level":1,"score":0.2264593541622162},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.21126484870910645},{"id":"https://openalex.org/C165801399","wikidata":"https://www.wikidata.org/wiki/Q25428","display_name":"Voltage","level":2,"score":0.074128657579422}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3704814.3706585","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3704814.3706585","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 8th International Conference on Computer Science and Application Engineering","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/W3004880366","https://openalex.org/W3164731488","https://openalex.org/W4200061596","https://openalex.org/W4291511524","https://openalex.org/W4293318214","https://openalex.org/W4313282129","https://openalex.org/W4318815111","https://openalex.org/W4386076039","https://openalex.org/W4396793960","https://openalex.org/W6600424091"],"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":{"The":[0,58],"escalator":[1,74,113],"system,":[2],"which":[3,151],"experiences":[4],"data":[5,43,62,75,94,103,188],"fluctuations":[6,41],"during":[7],"continuous":[8],"daily":[9],"operation,":[10],"plays":[11],"a":[12,153],"vital":[13],"role":[14],"in":[15,42,112,219],"subway":[16],"stations.":[17],"To":[18,35],"accurately":[19],"assess":[20],"the":[21,25,37,46,50,61,72,92,98,106,123,128,135,148,160,166,171,176,183,196,207],"health":[22],"status":[23],"of":[24,39,101,109,157,178,221],"escalator,":[26],"it":[27],"is":[28,56],"crucial":[29],"to":[30,126,168],"predict":[31],"its":[32],"future":[33],"condition.":[34],"mitigate":[36],"effects":[38,100],"significant":[40],"and":[44,78,81,96,137,175,201,227],"leverage":[45],"correlations":[47],"among":[48],"cross-variables,":[49],"Multi-scale":[51],"Average":[52],"Pool":[53],"Transformer":[54],"(MA-Transformer)":[55],"proposed.":[57],"model":[59,127,167],"pre-processes":[60],"using":[63],"average":[64,142],"pooling":[65,143],"layers":[66,144],"with":[67,85],"different":[68,141],"kernel":[69],"sizes,":[70],"segregates":[71],"intricate":[73],"into":[76,147],"trend":[77,173],"residual":[79],"components,":[80],"predicts":[82],"them":[83],"separately":[84],"two":[86,118],"independent":[87],"networks.":[88],"This":[89,164,185],"approach":[90],"enhances":[91],"essential":[93],"representations":[95],"mitigates":[97],"adverse":[99],"frequent":[102],"fluctuations.":[104],"Given":[105],"substantial":[107],"number":[108],"variable":[110,132],"types":[111],"data,":[114],"this":[115],"paper":[116],"introduces":[117],"modules":[119],"that":[120,180,206],"focus":[121],"on":[122],"self-attention":[124,149],"mechanism":[125],"inter-relationships":[129],"between":[130],"multiple":[131],"types.":[133],"Additionally,":[134],"trends":[136],"residuals":[138],"output":[139],"from":[140,182,189,192],"are":[145],"fed":[146],"layer,":[150],"provides":[152],"more":[154],"comprehensive":[155],"representation":[156],"features":[158],"at":[159,195],"same":[161],"time":[162],"point.":[163],"enables":[165],"better":[169],"capture":[170],"overall":[172],"changes":[174],"distribution":[177],"anomalies":[179],"deviate":[181],"trend.":[184],"study":[186],"collected":[187],"19":[190],"classes":[191],"2":[193],"escalators":[194],"engineering":[197],"site":[198],"for":[199],"training":[200],"testing.":[202],"Experimental":[203],"results":[204],"demonstrate":[205],"MA-Transformer":[208],"achieves":[209],"superior":[210],"detection":[211],"accuracy,":[212],"outperforming":[213],"evaluated":[214],"time-series":[215],"prediction":[216],"baseline":[217],"models":[218],"terms":[220],"both":[222],"Mean":[223,229],"Absolute":[224],"Error":[225,231],"(MAE)":[226],"Root":[228],"Square":[230],"(RMSE).":[232]},"counts_by_year":[{"year":2026,"cited_by_count":1}],"updated_date":"2026-03-27T05:58:40.876381","created_date":"2025-10-10T00:00:00"}
