{"id":"https://openalex.org/W4287843394","doi":"https://doi.org/10.1109/cacre54574.2022.9834202","title":"Research on prediction model of National Railway Freight Volume based on GA-BP network","display_name":"Research on prediction model of National Railway Freight Volume based on GA-BP network","publication_year":2022,"publication_date":"2022-07-01","ids":{"openalex":"https://openalex.org/W4287843394","doi":"https://doi.org/10.1109/cacre54574.2022.9834202"},"language":"en","primary_location":{"id":"doi:10.1109/cacre54574.2022.9834202","is_oa":false,"landing_page_url":"https://doi.org/10.1109/cacre54574.2022.9834202","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2022 7th International Conference on Automation, Control and Robotics Engineering (CACRE)","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/A5090236391","display_name":"Shiqiang Gai","orcid":null},"institutions":[{"id":"https://openalex.org/I4210092944","display_name":"Dalian University","ror":"https://ror.org/00g2ypp58","country_code":"CN","type":"education","lineage":["https://openalex.org/I4210092944"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Shiqiang Gai","raw_affiliation_strings":["Dalian Meritime University,School of Science,Dalian,China","School of Science, Dalian Meritime University, Dalian, China"],"affiliations":[{"raw_affiliation_string":"Dalian Meritime University,School of Science,Dalian,China","institution_ids":["https://openalex.org/I4210092944"]},{"raw_affiliation_string":"School of Science, Dalian Meritime University, Dalian, China","institution_ids":["https://openalex.org/I4210092944"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100549222","display_name":"Haiyan Xie","orcid":null},"institutions":[{"id":"https://openalex.org/I4210092944","display_name":"Dalian University","ror":"https://ror.org/00g2ypp58","country_code":"CN","type":"education","lineage":["https://openalex.org/I4210092944"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Haiyan Xie","raw_affiliation_strings":["Dalian Meritime University,School of Science,Dalian,China","School of Science, Dalian Meritime University, Dalian, China"],"affiliations":[{"raw_affiliation_string":"Dalian Meritime University,School of Science,Dalian,China","institution_ids":["https://openalex.org/I4210092944"]},{"raw_affiliation_string":"School of Science, Dalian Meritime University, Dalian, China","institution_ids":["https://openalex.org/I4210092944"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5070176788","display_name":"Chenxing Jia","orcid":null},"institutions":[{"id":"https://openalex.org/I4210092944","display_name":"Dalian University","ror":"https://ror.org/00g2ypp58","country_code":"CN","type":"education","lineage":["https://openalex.org/I4210092944"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Chenxing Jia","raw_affiliation_strings":["Dalian Meritime University,School of Science,Dalian,China","School of Science, Dalian Meritime University, Dalian, China"],"affiliations":[{"raw_affiliation_string":"Dalian Meritime University,School of Science,Dalian,China","institution_ids":["https://openalex.org/I4210092944"]},{"raw_affiliation_string":"School of Science, Dalian Meritime University, Dalian, China","institution_ids":["https://openalex.org/I4210092944"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5090236391"],"corresponding_institution_ids":["https://openalex.org/I4210092944"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.07217923,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"49","issue":null,"first_page":"382","last_page":"386"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11344","display_name":"Traffic Prediction and Management Techniques","score":0.9208999872207642,"subfield":{"id":"https://openalex.org/subfields/2215","display_name":"Building and Construction"},"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/T11344","display_name":"Traffic Prediction and Management Techniques","score":0.9208999872207642,"subfield":{"id":"https://openalex.org/subfields/2215","display_name":"Building and Construction"},"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/volume","display_name":"Volume (thermodynamics)","score":0.6912124156951904},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.4675402045249939},{"id":"https://openalex.org/keywords/transport-engineering","display_name":"Transport engineering","score":0.4468381404876709},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.26706570386886597}],"concepts":[{"id":"https://openalex.org/C20556612","wikidata":"https://www.wikidata.org/wiki/Q4469374","display_name":"Volume (thermodynamics)","level":2,"score":0.6912124156951904},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.4675402045249939},{"id":"https://openalex.org/C22212356","wikidata":"https://www.wikidata.org/wiki/Q775325","display_name":"Transport engineering","level":1,"score":0.4468381404876709},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.26706570386886597},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0},{"id":"https://openalex.org/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/cacre54574.2022.9834202","is_oa":false,"landing_page_url":"https://doi.org/10.1109/cacre54574.2022.9834202","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2022 7th International Conference on Automation, Control and Robotics Engineering (CACRE)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.5699999928474426,"display_name":"Decent work and economic growth","id":"https://metadata.un.org/sdg/8"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":1,"referenced_works":["https://openalex.org/W2382329132"],"related_works":["https://openalex.org/W4391375266","https://openalex.org/W2748952813","https://openalex.org/W2390279801","https://openalex.org/W2358668433","https://openalex.org/W4396701345","https://openalex.org/W2376932109","https://openalex.org/W2001405890","https://openalex.org/W4396696052","https://openalex.org/W4402327032","https://openalex.org/W2382290278"],"abstract_inverted_index":{"The":[0,16,133],"establishment":[1],"of":[2,13,39,47,49,74],"freight":[3,18,35,61,90,159],"volume":[4,19,62,73,91,160],"forecasting":[5,20],"model":[6,21,110],"is":[7,63,83,97],"very":[8],"important":[9],"to":[10,68,85],"the":[11,34,40,44,70,87,114,151],"development":[12],"logistics":[14],"industry.":[15],"traditional":[17],"can":[22,30,111,119],"not":[23,31],"deal":[24,128],"with":[25,129],"nonlinear":[26,123,131],"problems":[27],"effectively":[28],"and":[29,52,59,106,116,126,147,154],"accurately":[32],"predict":[33,86],"volume.":[36],"In":[37,77],"view":[38],"above":[41],"problems,":[42],"GDP,":[43],"lump":[45],"sum":[46],"retail":[48],"consumer":[50],"goods":[51],"employment":[53],"are":[54],"taken":[55,64],"as":[56,65],"input":[57],"variables,":[58],"railway":[60,75,89],"output":[66],"variable":[67],"forecast":[69],"monthly":[71],"national":[72,88],"freight.":[76],"this":[78,109],"paper,":[79],"GA-BP":[80,138],"neural":[81,139],"network":[82,140],"established":[84],"based":[92],"on":[93,103],"BP":[94,107],"network,":[95,108],"which":[96,118,149],"optimised":[98],"by":[99],"genetic":[100,104],"algorithm.":[101],"Based":[102],"algorithm":[105],"further":[112],"optimize":[113],"weights":[115],"thresholds,":[117],"realize":[120],"more":[121],"powerful":[122],"mapping":[124],"ability":[125],"better":[127,145],"complex":[130],"problems.":[132],"experimental":[134],"results":[135,143],"show":[136],"that":[137],"model\u2019s":[141,152],"prediction":[142],"have":[144],"stability":[146],"accuracy,":[148],"testifies":[150],"feasibility":[153],"provides":[155],"a":[156],"reference":[157],"for":[158],"prediction.":[161]},"counts_by_year":[],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
