{"id":"https://openalex.org/W4312490663","doi":"https://doi.org/10.1504/ijaom.2022.10052792","title":"A comparative study of automobile sales forecasting with ARIMA, SARIMA and deep learning LSTM model","display_name":"A comparative study of automobile sales forecasting with ARIMA, SARIMA and deep learning LSTM model","publication_year":2022,"publication_date":"2022-01-01","ids":{"openalex":"https://openalex.org/W4312490663","doi":"https://doi.org/10.1504/ijaom.2022.10052792"},"language":"en","primary_location":{"id":"doi:10.1504/ijaom.2022.10052792","is_oa":false,"landing_page_url":"https://doi.org/10.1504/ijaom.2022.10052792","pdf_url":null,"source":{"id":"https://openalex.org/S155832970","display_name":"International Journal of Advanced Operations Management","issn_l":"1758-938X","issn":["1758-938X","1758-9398"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310317825","host_organization_name":"Inderscience Publishers","host_organization_lineage":["https://openalex.org/P4310317825"],"host_organization_lineage_names":["Inderscience Publishers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"International Journal of Advanced Operations Management","raw_type":"journal-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/A5004289060","display_name":"Sharath Kariya Shetty","orcid":null},"institutions":[{"id":"https://openalex.org/I57085157","display_name":"Sardar Patel University","ror":"https://ror.org/05kfstc28","country_code":"IN","type":"education","lineage":["https://openalex.org/I57085157"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"Sharath Kariya Shetty","raw_affiliation_strings":["Mechanical Engineering Department, Sardar Patel College of Engineering, Bhavan's Campus, Mumbai, India"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Mechanical Engineering Department, Sardar Patel College of Engineering, Bhavan's Campus, Mumbai, India","institution_ids":["https://openalex.org/I57085157"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5086786846","display_name":"Rajesh Buktar","orcid":null},"institutions":[{"id":"https://openalex.org/I57085157","display_name":"Sardar Patel University","ror":"https://ror.org/05kfstc28","country_code":"IN","type":"education","lineage":["https://openalex.org/I57085157"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"Rajesh Buktar","raw_affiliation_strings":["Mechanical Engineering Department, Sardar Patel College of Engineering, Bhavan's Campus, Mumbai, India"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Mechanical Engineering Department, Sardar Patel College of Engineering, Bhavan's Campus, Mumbai, India","institution_ids":["https://openalex.org/I57085157"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I57085157"],"apc_list":null,"apc_paid":null,"fwci":0.49,"has_fulltext":false,"cited_by_count":3,"citation_normalized_percentile":{"value":0.68718068,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":96},"biblio":{"volume":"14","issue":"4","first_page":"366","last_page":"366"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11918","display_name":"Forecasting Techniques and Applications","score":0.9768000245094299,"subfield":{"id":"https://openalex.org/subfields/1803","display_name":"Management Science and Operations Research"},"field":{"id":"https://openalex.org/fields/18","display_name":"Decision Sciences"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},"topics":[{"id":"https://openalex.org/T11918","display_name":"Forecasting Techniques and Applications","score":0.9768000245094299,"subfield":{"id":"https://openalex.org/subfields/1803","display_name":"Management Science and Operations Research"},"field":{"id":"https://openalex.org/fields/18","display_name":"Decision Sciences"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/autoregressive-integrated-moving-average","display_name":"Autoregressive integrated moving average","score":0.9159110188484192},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.692679762840271},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5584269165992737},{"id":"https://openalex.org/keywords/sales-forecasting","display_name":"Sales forecasting","score":0.4970226585865021},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.49490827322006226},{"id":"https://openalex.org/keywords/econometrics","display_name":"Econometrics","score":0.4359092712402344},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.4128609299659729},{"id":"https://openalex.org/keywords/time-series","display_name":"Time series","score":0.36770719289779663},{"id":"https://openalex.org/keywords/economics","display_name":"Economics","score":0.16036951541900635}],"concepts":[{"id":"https://openalex.org/C24338571","wikidata":"https://www.wikidata.org/wiki/Q2566298","display_name":"Autoregressive integrated moving average","level":3,"score":0.9159110188484192},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.692679762840271},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5584269165992737},{"id":"https://openalex.org/C2984642479","wikidata":"https://www.wikidata.org/wiki/Q7404320","display_name":"Sales forecasting","level":2,"score":0.4970226585865021},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.49490827322006226},{"id":"https://openalex.org/C149782125","wikidata":"https://www.wikidata.org/wiki/Q160039","display_name":"Econometrics","level":1,"score":0.4359092712402344},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.4128609299659729},{"id":"https://openalex.org/C151406439","wikidata":"https://www.wikidata.org/wiki/Q186588","display_name":"Time series","level":2,"score":0.36770719289779663},{"id":"https://openalex.org/C162324750","wikidata":"https://www.wikidata.org/wiki/Q8134","display_name":"Economics","level":0,"score":0.16036951541900635}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1504/ijaom.2022.10052792","is_oa":false,"landing_page_url":"https://doi.org/10.1504/ijaom.2022.10052792","pdf_url":null,"source":{"id":"https://openalex.org/S155832970","display_name":"International Journal of Advanced Operations Management","issn_l":"1758-938X","issn":["1758-938X","1758-9398"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310317825","host_organization_name":"Inderscience Publishers","host_organization_lineage":["https://openalex.org/P4310317825"],"host_organization_lineage_names":["Inderscience Publishers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"International Journal of Advanced Operations Management","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":["https://openalex.org/W4380075502","https://openalex.org/W4223943233","https://openalex.org/W4312200629","https://openalex.org/W4360585206","https://openalex.org/W4364306694","https://openalex.org/W4380086463","https://openalex.org/W4225161397","https://openalex.org/W3014300295","https://openalex.org/W3164822677","https://openalex.org/W2795261237"],"abstract_inverted_index":{"In":[0,82],"deciding":[1],"production-plan,":[2],"material-inventory,":[3],"scheduling,":[4],"etcetera":[5],"of":[6,12,68,79,130],"an":[7,64,99],"automobile":[8,26,101],"industry,":[9,27],"the":[10,25,42,46,51,75,80,88,92,128,150,155],"accuracy":[11,90,129],"forecasting":[13,22],"techniques":[14,23,97],"plays":[15],"a":[16,146],"very":[17],"important":[18],"role.":[19],"The":[20,103],"quantitative":[21],"in":[24,45,54,145],"conventional":[28],"methods":[29],"like":[30],"auto-regressive,":[31],"ARIMA,":[32,93],"and":[33,56,60,77,95,115,148],"seasonal-ARIMA":[34],"are":[35],"not":[36],"accurate":[37],"enough":[38],"to":[39],"extract":[40],"all":[41],"information":[43],"hidden":[44],"time":[47,69],"series":[48,70],"data.":[49,81,156],"With":[50],"recent":[52],"developments":[53],"machine-learning":[55],"deep":[57,104,131],"learning,":[58],"RNN":[59],"LSTM":[61,96,107],"can":[62,133],"produce":[63],"impressive":[65],"result":[66],"out":[67],"data":[71],"by":[72,109,116,136],"dealing":[73],"with":[74,113,120],"nonlinearity":[76],"complexity":[78],"this":[83],"study,":[84],"we":[85],"have":[86],"compared":[87,112,119],"prediction":[89],"among":[91],"SARIMA,":[94],"for":[98,154],"Indian":[100],"company.":[102],"learning":[105,132,141],"model":[106],"outperforms":[108],"92%":[110],"when":[111,118],"ARIMA":[114],"42.5%":[117],"SARIMA":[121],"techniques.":[122],"Moreover,":[123],"it":[124],"is":[125],"noticed":[126],"that":[127],"be":[134],"improved":[135],"tuning":[137],"hyperparameters":[138],"such":[139],"as":[140],"rate,":[142],"neuron":[143],"number":[144],"layer,":[147],"choosing":[149],"correct":[151],"weight":[152],"initialiser":[153]},"counts_by_year":[{"year":2025,"cited_by_count":2},{"year":2024,"cited_by_count":1}],"updated_date":"2026-01-15T23:16:33.117629","created_date":"2025-10-10T00:00:00"}
