{"id":"https://openalex.org/W7204180456","doi":"https://doi.org/10.51483/ijaiml.6.2.2026.209-228","title":"Machine Learning Based Software Effort Estimation In Agile Based Projects By Using Scrumban Methodologies","display_name":"Machine Learning Based Software Effort Estimation In Agile Based Projects By Using Scrumban Methodologies","publication_year":2026,"publication_date":"2026-01-01","ids":{"openalex":"https://openalex.org/W7204180456","doi":"https://doi.org/10.51483/ijaiml.6.2.2026.209-228"},"language":"en","primary_location":{"id":"doi:10.51483/ijaiml.6.2.2026.209-228","doi":"https://doi.org/10.51483/ijaiml.6.2.2026.209-228","is_oa":true,"landing_page_url":"https://doi.org/10.51483/ijaiml.6.2.2026.209-228","pdf_url":"https://www.svedbergopen.com/index.php/ijaiml/article/download/1158/788","source":{"id":"https://openalex.org/S4386621846","display_name":"International Journal of Artificial Intelligence and Machine Learning","issn_l":"2789-2557","issn":["2789-2557"],"is_oa":false,"is_in_doaj":false,"is_core":true,"listed_in":["cwts-core"],"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"International Journal of Artificial Intelligence and Machine Learning","raw_type":"journal-article"},"volume":null,"type":"article","is_traditional":true,"indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"hybrid","oa_url":"https://www.svedbergopen.com/index.php/ijaiml/article/download/1158/788","any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5018244835","display_name":"B. V. Srikanth","orcid":"https://orcid.org/0009-0000-9004-1700","observed_orcids":["https://orcid.org/0009-0000-9004-1700"]},"institutions":[{"id":"https://openalex.org/I83737708","display_name":"REVA University","ror":"https://ror.org/03gtcxd54","country_code":"IN","type":"education","lineage":["https://openalex.org/I83737708"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"B. V Srikanth","raw_affiliation_strings":["Research Scholar , School of Computer Science and Engineering , REVA University , Bangalore , India"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Research Scholar , School of Computer Science and Engineering , REVA University , Bangalore , India","institution_ids":["https://openalex.org/I83737708"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5097242234","display_name":"Bhaskar Reddy P. V.","orcid":null,"observed_orcids":[]},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Bhaskar Reddy P. V","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":true,"cited_by_count":0,"citation_normalized_percentile":{"value":0.0,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"6","issue":"2","first_page":"209","last_page":"228"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10430","display_name":"Software Engineering Techniques and Practices","score":0.9994999766349792,"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"}},"topics":[{"id":"https://openalex.org/T10430","display_name":"Software Engineering Techniques and Practices","score":0.9994999766349792,"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"}},{"id":"https://openalex.org/T10260","display_name":"Software Engineering Research","score":0.0003000000142492354,"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"}},{"id":"https://openalex.org/T11918","display_name":"Forecasting Techniques and Applications","score":0.0,"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/software-effort-estimation","display_name":"software effort estimation","score":0.9990000128746033},{"id":"https://openalex.org/keywords/agile-software-development","display_name":"agile software development","score":0.8769999742507935},{"id":"https://openalex.org/keywords/scrumban","display_name":"Scrumban","score":0.9409999847412109},{"id":"https://openalex.org/keywords/scrum","display_name":"Scrum","score":0.9599999785423279},{"id":"https://openalex.org/keywords/kanban","display_name":"Kanban","score":0.9919999837875366},{"id":"https://openalex.org/keywords/story-points","display_name":"story points","score":0.7609999775886536},{"id":"https://openalex.org/keywords/sprint-speed","display_name":"sprint speed","score":0.9940000176429749},{"id":"https://openalex.org/keywords/backlog-management","display_name":"backlog management","score":0.7490000128746033},{"id":"https://openalex.org/keywords/random-forest","display_name":"random forest","score":0.5630000233650208},{"id":"https://openalex.org/keywords/support-vector-regression","display_name":"support vector regression","score":0.9929999709129333},{"id":"https://openalex.org/keywords/gradient-boosting-regression","display_name":"gradient boosting regression","score":0.9660000205039978},{"id":"https://openalex.org/keywords/project-complexity","display_name":"project complexity","score":0.8050000071525574}],"concepts":[{"id":"https://openalex.org/C14185376","wikidata":"https://www.wikidata.org/wiki/Q30232","display_name":"Agile software development","level":2,"score":0.6948999762535095},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5195000171661377},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.47609999775886536},{"id":"https://openalex.org/C529173508","wikidata":"https://www.wikidata.org/wiki/Q638608","display_name":"Software development","level":3,"score":0.4584999978542328},{"id":"https://openalex.org/C2777904410","wikidata":"https://www.wikidata.org/wiki/Q7397","display_name":"Software","level":2,"score":0.4555000066757202},{"id":"https://openalex.org/C2776868573","wikidata":"https://www.wikidata.org/wiki/Q46855","display_name":"Sprint","level":2,"score":0.44920000433921814},{"id":"https://openalex.org/C15952604","wikidata":"https://www.wikidata.org/wiki/Q179012","display_name":"Project management","level":2,"score":0.43689998984336853},{"id":"https://openalex.org/C180152950","wikidata":"https://www.wikidata.org/wiki/Q2904257","display_name":"Software development process","level":4,"score":0.3612000048160553},{"id":"https://openalex.org/C207701116","wikidata":"https://www.wikidata.org/wiki/Q7901734","display_name":"Use Case Points","level":5,"score":0.3515999913215637},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.33730000257492065},{"id":"https://openalex.org/C87813535","wikidata":"https://www.wikidata.org/wiki/Q956418","display_name":"Agile Unified Process","level":5,"score":0.33309999108314514},{"id":"https://openalex.org/C177212765","wikidata":"https://www.wikidata.org/wiki/Q627335","display_name":"Workflow","level":2,"score":0.32519999146461487},{"id":"https://openalex.org/C147579259","wikidata":"https://www.wikidata.org/wiki/Q460387","display_name":"Scrum","level":4,"score":0.3140999972820282},{"id":"https://openalex.org/C96250715","wikidata":"https://www.wikidata.org/wiki/Q965330","display_name":"Estimation","level":2,"score":0.30489999055862427},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.2973000109195709},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.28209999203681946},{"id":"https://openalex.org/C70153297","wikidata":"https://www.wikidata.org/wiki/Q5591907","display_name":"Gradient boosting","level":3,"score":0.2806999981403351},{"id":"https://openalex.org/C115903868","wikidata":"https://www.wikidata.org/wiki/Q80993","display_name":"Software engineering","level":1,"score":0.2757999897003174},{"id":"https://openalex.org/C201995342","wikidata":"https://www.wikidata.org/wiki/Q682496","display_name":"Systems engineering","level":1,"score":0.27399998903274536},{"id":"https://openalex.org/C139945424","wikidata":"https://www.wikidata.org/wiki/Q1940696","display_name":"Mean squared error","level":2,"score":0.2669999897480011},{"id":"https://openalex.org/C40919944","wikidata":"https://www.wikidata.org/wiki/Q947779","display_name":"Software project management","level":5,"score":0.26570001244544983},{"id":"https://openalex.org/C36464697","wikidata":"https://www.wikidata.org/wiki/Q451553","display_name":"Visualization","level":2,"score":0.2628999948501587},{"id":"https://openalex.org/C13736549","wikidata":"https://www.wikidata.org/wiki/Q4489420","display_name":"Industrial engineering","level":1,"score":0.25999999046325684},{"id":"https://openalex.org/C2779343474","wikidata":"https://www.wikidata.org/wiki/Q3109175","display_name":"Context (archaeology)","level":2,"score":0.259799987077713}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.51483/ijaiml.6.2.2026.209-228","doi":"https://doi.org/10.51483/ijaiml.6.2.2026.209-228","is_oa":true,"landing_page_url":"https://doi.org/10.51483/ijaiml.6.2.2026.209-228","pdf_url":"https://www.svedbergopen.com/index.php/ijaiml/article/download/1158/788","source":{"id":"https://openalex.org/S4386621846","display_name":"International Journal of Artificial Intelligence and Machine Learning","issn_l":"2789-2557","issn":["2789-2557"],"is_oa":false,"is_in_doaj":false,"is_core":true,"listed_in":["cwts-core"],"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"International Journal of Artificial Intelligence and Machine Learning","raw_type":"journal-article"}],"best_oa_location":{"id":"doi:10.51483/ijaiml.6.2.2026.209-228","doi":"https://doi.org/10.51483/ijaiml.6.2.2026.209-228","is_oa":true,"landing_page_url":"https://doi.org/10.51483/ijaiml.6.2.2026.209-228","pdf_url":"https://www.svedbergopen.com/index.php/ijaiml/article/download/1158/788","source":{"id":"https://openalex.org/S4386621846","display_name":"International Journal of Artificial Intelligence and Machine Learning","issn_l":"2789-2557","issn":["2789-2557"],"is_oa":false,"is_in_doaj":false,"is_core":true,"listed_in":["cwts-core"],"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"International Journal of Artificial Intelligence and Machine Learning","raw_type":"journal-article"},"sustainable_development_goals":[],"study_designs":[],"awards":[],"funders":[],"has_content":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W7204180456.pdf","grobid_xml":"https://content.openalex.org/works/W7204180456.grobid-xml"},"referenced_works_count":13,"referenced_works":["https://openalex.org/W3083583628","https://openalex.org/W3158075067","https://openalex.org/W3217418390","https://openalex.org/W4288080364","https://openalex.org/W4310266629","https://openalex.org/W4312045253","https://openalex.org/W4319599802","https://openalex.org/W4323650410","https://openalex.org/W4327969900","https://openalex.org/W4383503459","https://openalex.org/W4403022025","https://openalex.org/W7131468242","https://openalex.org/W7133309516"],"related_works":["https://openalex.org/W2999958824","https://openalex.org/W3217418390","https://openalex.org/W3215021373","https://openalex.org/W7133309516","https://openalex.org/W3158711551","https://openalex.org/W2512697187","https://openalex.org/W2883613716","https://openalex.org/W7124306050","https://openalex.org/W4286215804","https://openalex.org/W2899803392"],"abstract_inverted_index":{"Effort":[0,65],"estimation":[1,47,90,172,217],"in":[2,7,35,145,227],"software":[3,13,143,229],"development":[4,14,230],"is":[5,209],"important":[6],"the":[8,18,22,25,28,36,142,161,164,212,223],"context":[9],"of":[10,21,27,45,157,163,204],"an":[11],"Agile":[12,96,158,205,228],"process":[15],"due":[16],"to":[17,33,88,140,198,201],"changing":[19],"requirements":[20],"customers":[23],"and":[24,38,79,86,92,112,132,138,178,195,222],"dynamics":[26],"business":[29],"environment,":[30],"which":[31],"leads":[32],"uncertainties":[34],"planning":[37,78,220],"resource":[39],"management":[40,81],"process.":[41],"The":[42,72,147,168],"conventional":[43],"techniques":[44],"effort":[46,144],"do":[48],"not":[49],"yield":[50],"accurate":[51],"predictions.":[52],"This":[53],"study":[54],"proposes":[55],"a":[56,61],"novel":[57],"Multi":[58],"Learning-Scrumban":[59],"Framework,":[60],"Machine":[62],"Learning-based":[63],"Software":[64],"Estimation":[66],"model":[67,118],"integrated":[68],"with":[69,82],"Scrumban":[70],"methodologies.":[71],"proposed":[73,165,213],"framework":[74,169,214],"combines":[75],"Scrum-based":[76],"sprint":[77,219],"backlog":[80],"Kanban":[83],"workflow":[84],"visualization":[85],"monitoring":[87],"enhance":[89],"accuracy":[91],"project":[93,97,225],"adaptability.":[94],"Historical":[95],"datasets":[98],"containing":[99],"Story":[100],"Points,":[101],"Sprint":[102,110],"Velocity,":[103],"Team":[104],"Experience,":[105],"Project":[106],"Complexity,":[107],"Backlog":[108],"Size,":[109],"Duration,":[111],"Requirement":[113],"Volatility":[114],"were":[115,136],"utilized":[116],"for":[117,152],"development.":[119],"Various":[120],"advanced":[121],"machine":[122],"learning":[123],"models":[124],"such":[125],"as":[126],"Random":[127],"Forest,":[128],"Support":[129],"Vector":[130],"Regression,":[131],"Gradient":[133],"Boosting":[134],"Regression":[135],"developed":[137],"tuned":[139],"estimate":[141],"person-hours.":[146],"experimental":[148],"assessment":[149],"carried":[150],"out":[151],"more":[153],"than":[154],"1,500":[155],"cases":[156],"projects":[159],"showed":[160],"efficiency":[162,221],"ML-SCRUMBAN":[166],"Framework.":[167],"provided":[170],"96.82%":[171],"accuracy,":[173,218],"96.31%":[174],"precision,":[175],"95.88%":[176],"recall":[177],"96.09%":[179],"F1-score.":[180],"Additionally,":[181],"it":[182,208],"decreased":[183],"Mean":[184,190],"Absolute":[185],"Error":[186,192],"by":[187,193],"38.9%,":[188],"Root":[189],"Square":[191],"37.3%":[194],"increased":[196],"PRED(25)":[197],"98.74%":[199],"compared":[200],"traditional":[202],"methods":[203],"estimation.":[206],"Thus,":[207],"evident":[210],"that":[211],"substantially":[215],"improves":[216],"general":[224],"performance":[226],"environment.":[231]},"counts_by_year":[],"updated_date":"2026-11-04T10:54:05.112534","created_date":"2026-08-26T00:00:00"}
