{"id":"https://openalex.org/W7161571665","doi":"https://doi.org/10.31449/inf.v50i13.12921","title":"Financial Forecasting and Budget Management Based on Machine Learning","display_name":"Financial Forecasting and Budget Management Based on Machine Learning","publication_year":2026,"publication_date":"2026-05-18","ids":{"openalex":"https://openalex.org/W7161571665","doi":"https://doi.org/10.31449/inf.v50i13.12921"},"language":null,"primary_location":{"id":"doi:10.31449/inf.v50i13.12921","is_oa":true,"landing_page_url":"https://doi.org/10.31449/inf.v50i13.12921","pdf_url":"https://www.informatica.si/index.php/informatica/article/download/12921/6711","source":{"id":"https://openalex.org/S4210173311","display_name":"Informatica","issn_l":"0350-5596","issn":["0350-5596","1854-3871"],"is_oa":true,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310314525","host_organization_name":"Slovenian Society Informatika","host_organization_lineage":["https://openalex.org/P4310314525"],"host_organization_lineage_names":["Slovenian Society Informatika"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Informatica","raw_type":"journal-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"diamond","oa_url":"https://www.informatica.si/index.php/informatica/article/download/12921/6711","any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5136418308","display_name":"Linmeng Liu","orcid":null},"institutions":[{"id":"https://openalex.org/I24185976","display_name":"Sichuan University","ror":"https://ror.org/011ashp19","country_code":"CN","type":"education","lineage":["https://openalex.org/I24185976"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Linmeng Liu","raw_affiliation_strings":["Business School , Geely University of china , Chengdu , Sichuan , 641423 , China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Business School , Geely University of china , Chengdu , Sichuan , 641423 , China","institution_ids":["https://openalex.org/I24185976"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":["https://openalex.org/A5136418308"],"corresponding_institution_ids":["https://openalex.org/I24185976"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":true,"cited_by_count":0,"citation_normalized_percentile":{"value":0.61348089,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"50","issue":"13","first_page":null,"last_page":null},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11653","display_name":"Financial Distress and Bankruptcy Prediction","score":0.20399999618530273,"subfield":{"id":"https://openalex.org/subfields/1402","display_name":"Accounting"},"field":{"id":"https://openalex.org/fields/14","display_name":"Business, Management and Accounting"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},"topics":[{"id":"https://openalex.org/T11653","display_name":"Financial Distress and Bankruptcy Prediction","score":0.20399999618530273,"subfield":{"id":"https://openalex.org/subfields/1402","display_name":"Accounting"},"field":{"id":"https://openalex.org/fields/14","display_name":"Business, Management and Accounting"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},{"id":"https://openalex.org/T11326","display_name":"Stock Market Forecasting Methods","score":0.09759999811649323,"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"}},{"id":"https://openalex.org/T14413","display_name":"Advanced Technologies in Various Fields","score":0.03539999946951866,"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/artificial-neural-network","display_name":"Artificial neural network","score":0.647599995136261},{"id":"https://openalex.org/keywords/backpropagation","display_name":"Backpropagation","score":0.529699981212616},{"id":"https://openalex.org/keywords/scalability","display_name":"Scalability","score":0.4699000120162964},{"id":"https://openalex.org/keywords/scheduling","display_name":"Scheduling (production processes)","score":0.39579999446868896},{"id":"https://openalex.org/keywords/autoencoder","display_name":"Autoencoder","score":0.34950000047683716},{"id":"https://openalex.org/keywords/predictive-modelling","display_name":"Predictive modelling","score":0.3278000056743622},{"id":"https://openalex.org/keywords/construct","display_name":"Construct (python library)","score":0.3131999969482422},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.31279999017715454}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.736299991607666},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6546000242233276},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.6478000283241272},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.647599995136261},{"id":"https://openalex.org/C155032097","wikidata":"https://www.wikidata.org/wiki/Q798503","display_name":"Backpropagation","level":3,"score":0.529699981212616},{"id":"https://openalex.org/C48044578","wikidata":"https://www.wikidata.org/wiki/Q727490","display_name":"Scalability","level":2,"score":0.4699000120162964},{"id":"https://openalex.org/C206729178","wikidata":"https://www.wikidata.org/wiki/Q2271896","display_name":"Scheduling (production processes)","level":2,"score":0.39579999446868896},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.373199999332428},{"id":"https://openalex.org/C101738243","wikidata":"https://www.wikidata.org/wiki/Q786435","display_name":"Autoencoder","level":3,"score":0.34950000047683716},{"id":"https://openalex.org/C45804977","wikidata":"https://www.wikidata.org/wiki/Q7239673","display_name":"Predictive modelling","level":2,"score":0.3278000056743622},{"id":"https://openalex.org/C2780801425","wikidata":"https://www.wikidata.org/wiki/Q5164392","display_name":"Construct (python library)","level":2,"score":0.3131999969482422},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.31279999017715454},{"id":"https://openalex.org/C67186912","wikidata":"https://www.wikidata.org/wiki/Q367664","display_name":"Data modeling","level":2,"score":0.29739999771118164},{"id":"https://openalex.org/C75684735","wikidata":"https://www.wikidata.org/wiki/Q858810","display_name":"Big data","level":2,"score":0.2888999879360199},{"id":"https://openalex.org/C506796395","wikidata":"https://www.wikidata.org/wiki/Q4738155","display_name":"Financial management","level":2,"score":0.28769999742507935},{"id":"https://openalex.org/C72108876","wikidata":"https://www.wikidata.org/wiki/Q844565","display_name":"Transaction processing","level":3,"score":0.2777999937534332},{"id":"https://openalex.org/C23925645","wikidata":"https://www.wikidata.org/wiki/Q5449731","display_name":"Financial modeling","level":2,"score":0.2759000062942505},{"id":"https://openalex.org/C29202148","wikidata":"https://www.wikidata.org/wiki/Q287260","display_name":"Resource allocation","level":2,"score":0.27239999175071716},{"id":"https://openalex.org/C138827492","wikidata":"https://www.wikidata.org/wiki/Q6661985","display_name":"Data processing","level":2,"score":0.2687000036239624},{"id":"https://openalex.org/C10138342","wikidata":"https://www.wikidata.org/wiki/Q43015","display_name":"Finance","level":1,"score":0.2669000029563904},{"id":"https://openalex.org/C139043278","wikidata":"https://www.wikidata.org/wiki/Q837171","display_name":"Financial services","level":2,"score":0.2628999948501587},{"id":"https://openalex.org/C106131492","wikidata":"https://www.wikidata.org/wiki/Q3072260","display_name":"Filter (signal processing)","level":2,"score":0.2606000006198883},{"id":"https://openalex.org/C76073288","wikidata":"https://www.wikidata.org/wiki/Q1337875","display_name":"Financial risk","level":2,"score":0.2605000138282776},{"id":"https://openalex.org/C75949130","wikidata":"https://www.wikidata.org/wiki/Q848010","display_name":"Database transaction","level":2,"score":0.2547999918460846}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.31449/inf.v50i13.12921","is_oa":true,"landing_page_url":"https://doi.org/10.31449/inf.v50i13.12921","pdf_url":"https://www.informatica.si/index.php/informatica/article/download/12921/6711","source":{"id":"https://openalex.org/S4210173311","display_name":"Informatica","issn_l":"0350-5596","issn":["0350-5596","1854-3871"],"is_oa":true,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310314525","host_organization_name":"Slovenian Society Informatika","host_organization_lineage":["https://openalex.org/P4310314525"],"host_organization_lineage_names":["Slovenian Society Informatika"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Informatica","raw_type":"journal-article"}],"best_oa_location":{"id":"doi:10.31449/inf.v50i13.12921","is_oa":true,"landing_page_url":"https://doi.org/10.31449/inf.v50i13.12921","pdf_url":"https://www.informatica.si/index.php/informatica/article/download/12921/6711","source":{"id":"https://openalex.org/S4210173311","display_name":"Informatica","issn_l":"0350-5596","issn":["0350-5596","1854-3871"],"is_oa":true,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310314525","host_organization_name":"Slovenian Society Informatika","host_organization_lineage":["https://openalex.org/P4310314525"],"host_organization_lineage_names":["Slovenian Society Informatika"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Informatica","raw_type":"journal-article"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W7161571665.pdf","grobid_xml":"https://content.openalex.org/works/W7161571665.grobid-xml"},"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"This":[0],"article":[1],"focuses":[2],"on":[3],"the":[4,18,29,57,81,84,103,107],"application":[5],"of":[6,24,31,37,83,113,129,131],"machine":[7],"learning":[8],"technology":[9],"in":[10,35,111],"financial":[11,26,33,71],"forecasting":[12],"and":[13,21,43,93,116,118,145,149],"budget":[14],"management":[15],"to":[16,67,74],"improve":[17],"intelligence":[19],"level":[20],"decision-making":[22],"efficiency":[23],"enterprise":[25],"management.":[27],"Given":[28],"shortcomings":[30],"traditional":[32,94],"models":[34,110],"terms":[36,112],"data":[38],"processing":[39,127],"capability,":[40],"prediction":[41,72,114,121],"accuracy,":[42],"response":[44],"speed,":[45],"an":[46],"improved":[47,85,104],"Sparse":[48],"Denoising":[49],"Autoencoder":[50],"(SDAE)":[51],"neural":[52,96],"network":[53],"is":[54],"introduced":[55],"as":[56],"core":[58],"modeling":[59],"tool.":[60],"And":[61],"by":[62],"using":[63],"interval":[64],"discretization":[65],"method":[66],"construct":[68],"a":[69],"robust":[70],"model":[73,87],"achieve":[75],"anomaly":[76],"smoothing.":[77],"Through":[78],"comparative":[79],"experiments,":[80],"performance":[82],"SDAE":[86,92,105],"was":[88],"compared":[89],"with":[90],"standard":[91],"backpropagation":[95],"networks":[97],"(BPNN).":[98],"The":[99],"results":[100],"indicate":[101],"that":[102,140],"outperforms":[106],"other":[108],"two":[109],"accuracy":[115],"stability,":[117],"can":[119,150],"complete":[120],"tasks":[122],"within":[123],"milliseconds":[124],"even":[125],"when":[126],"tens":[128],"thousands":[130],"records.":[132],"In":[133],"addition,":[134],"system":[135],"concurrency":[136],"testing":[137],"has":[138,142],"shown":[139],"it":[141],"good":[143],"scalability":[144],"resource":[146],"scheduling":[147],"capabilities,":[148],"support":[151],"multi":[152],"departmental":[153],"parallel":[154],"usage":[155],"scenarios.":[156]},"counts_by_year":[],"updated_date":"2026-05-21T06:26:12.895304","created_date":"2026-05-19T00:00:00"}
