{"id":"https://openalex.org/W4402454395","doi":"https://doi.org/10.1145/3674029.3674036","title":"Comparative Study of Machine Learning Techniques for Inventory Classification Based on Multi-Criteria Decision-Making","display_name":"Comparative Study of Machine Learning Techniques for Inventory Classification Based on Multi-Criteria Decision-Making","publication_year":2024,"publication_date":"2024-05-24","ids":{"openalex":"https://openalex.org/W4402454395","doi":"https://doi.org/10.1145/3674029.3674036"},"language":"en","primary_location":{"id":"doi:10.1145/3674029.3674036","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3674029.3674036","pdf_url":null,"source":null,"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2024 9th International Conference on Machine Learning Technologies (ICMLT)","raw_type":"proceedings-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://doi.org/10.1145/3674029.3674036","any_repository_has_fulltext":null},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5018204443","display_name":"Busaba Phruksaphanrat","orcid":"https://orcid.org/0000-0002-3600-2943"},"institutions":[{"id":"https://openalex.org/I108108428","display_name":"Thammasat University","ror":"https://ror.org/002yp7f20","country_code":"TH","type":"education","lineage":["https://openalex.org/I108108428"]}],"countries":["TH"],"is_corresponding":true,"raw_author_name":"Busaba Phruksaphanrat","raw_affiliation_strings":["Industrial Engineering Department, Thammasat University, Faculty of Engineering,Thammasat School of Engineering, Thailand"],"raw_orcid":"https://orcid.org/0000-0002-3600-2943","affiliations":[{"raw_affiliation_string":"Industrial Engineering Department, Thammasat University, Faculty of Engineering,Thammasat School of Engineering, Thailand","institution_ids":["https://openalex.org/I108108428"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":["https://openalex.org/A5018204443"],"corresponding_institution_ids":["https://openalex.org/I108108428"],"apc_list":null,"apc_paid":null,"fwci":0.9386,"has_fulltext":false,"cited_by_count":2,"citation_normalized_percentile":{"value":0.78192625,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":91,"max":98},"biblio":{"volume":null,"issue":null,"first_page":"36","last_page":"40"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11918","display_name":"Forecasting Techniques and Applications","score":0.8605999946594238,"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":0.8605999946594238,"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/T11443","display_name":"Advanced Statistical Process Monitoring","score":0.8398000001907349,"subfield":{"id":"https://openalex.org/subfields/1804","display_name":"Statistics, Probability and Uncertainty"},"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/T10320","display_name":"Neural Networks and Applications","score":0.8241000175476074,"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/computer-science","display_name":"Computer science","score":0.7446084022521973},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.6657328009605408},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6177959442138672},{"id":"https://openalex.org/keywords/decision-tree","display_name":"Decision tree","score":0.4749981164932251},{"id":"https://openalex.org/keywords/support-vector-machine","display_name":"Support vector machine","score":0.41123050451278687}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7446084022521973},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.6657328009605408},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6177959442138672},{"id":"https://openalex.org/C84525736","wikidata":"https://www.wikidata.org/wiki/Q831366","display_name":"Decision tree","level":2,"score":0.4749981164932251},{"id":"https://openalex.org/C12267149","wikidata":"https://www.wikidata.org/wiki/Q282453","display_name":"Support vector machine","level":2,"score":0.41123050451278687}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3674029.3674036","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3674029.3674036","pdf_url":null,"source":null,"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2024 9th International Conference on Machine Learning Technologies (ICMLT)","raw_type":"proceedings-article"}],"best_oa_location":{"id":"doi:10.1145/3674029.3674036","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3674029.3674036","pdf_url":null,"source":null,"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2024 9th International Conference on Machine Learning Technologies (ICMLT)","raw_type":"proceedings-article"},"sustainable_development_goals":[{"score":0.7599999904632568,"id":"https://metadata.un.org/sdg/16","display_name":"Peace, Justice and strong institutions"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":19,"referenced_works":["https://openalex.org/W607505555","https://openalex.org/W872145508","https://openalex.org/W1971038102","https://openalex.org/W1979258690","https://openalex.org/W1984425262","https://openalex.org/W1998835069","https://openalex.org/W2017157407","https://openalex.org/W2034960640","https://openalex.org/W2053652165","https://openalex.org/W2056736038","https://openalex.org/W2082286494","https://openalex.org/W2093228212","https://openalex.org/W2415375246","https://openalex.org/W2597133720","https://openalex.org/W2620495529","https://openalex.org/W3020848637","https://openalex.org/W3149022113","https://openalex.org/W4298395456","https://openalex.org/W4381686442"],"related_works":["https://openalex.org/W2961085424","https://openalex.org/W4306674287","https://openalex.org/W3046775127","https://openalex.org/W3107602296","https://openalex.org/W4394896187","https://openalex.org/W3170094116","https://openalex.org/W4386462264","https://openalex.org/W4364306694","https://openalex.org/W4312192474","https://openalex.org/W4224922629"],"abstract_inverted_index":{"Various":[0],"multicriteria":[1,81,114],"inventory":[2,46,82,98,135,147,158],"classification":[3,99,131],"methods":[4,32],"have":[5],"been":[6],"developed":[7],"to":[8,65,179],"overcome":[9],"the":[10,20,41,49,60,70,95,108,113,130,133,138,144,154,172,186,194],"limitations":[11],"of":[12,51,56,62,97,132,137,199],"conventional":[13],"ABC":[14,122],"analysis.":[15],"Commonly":[16],"used":[17],"techniques":[18,79,178],"include":[19],"analytic":[21],"hierarchy":[22],"process":[23],"(AHP)":[24],"and":[25,48,90,103,125,149,164,202,207,213],"data":[26,201],"envelopment":[27],"analysis":[28,162],"(DEA).":[29],"However,":[30],"these":[31],"are":[33],"mainly":[34],"focused":[35],"on":[36,107,143],"classifying":[37],"existing":[38,102,109],"items":[39,68,105,136],"in":[40,69,129,157],"inventory.":[42],"Furthermore,":[43],"both":[44,88,101],"total":[45,91,146],"costs":[47],"similarity":[50,89,150],"each":[52],"group":[53],"should":[54],"be":[55,180],"concern.":[57],"To":[58,152],"address":[59],"challenge":[61],"assigning":[63],"groups":[64,110],"new,":[66],"unclassified":[67],"warehouse,":[71],"this":[72],"research":[73],"proposes":[74],"integrating":[75],"machine":[76,175],"learning":[77,176],"(ML)":[78,177],"with":[80,193],"classification.":[83],"The":[84,116],"combined":[85],"approach":[86],"considers":[87],"costs,":[92],"thereby":[93],"improving":[94],"accuracy":[96,156,196],"for":[100,209],"new":[104],"based":[106,142],"classified":[111],"using":[112],"approach.":[115],"result":[117],"has":[118],"shown":[119],"that":[120],"among":[121],"analysis,":[123],"DEA,":[124],"AHP;":[126],"AHP":[127],"outperforms":[128],"current":[134],"case":[139],"study":[140],"factory":[141],"minimum":[145],"cost":[148],"index.":[151],"achieve":[153],"highest":[155,195],"classification,":[159],"firstly":[160],"discriminant":[161],"(DA)":[163],"artificial":[165],"neural":[166],"network":[167],"(ANN)":[168],"were":[169],"identified":[170],"as":[171],"most":[173],"suitable":[174],"integrated.":[181],"After":[182],"tuning":[183],"some":[184],"parameters,":[185],"best":[187],"adjusted":[188],"ANN":[189],"model":[190],"was":[191],"found":[192],"at":[197,204],"97.70%":[198],"testing":[200],"F1":[203],"100%,":[205],"94.74%,":[206],"98.25%":[208],"classes":[210],"A,":[211],"B,":[212],"C,":[214],"respectively.":[215]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":1}],"updated_date":"2025-12-27T23:08:20.325037","created_date":"2025-10-10T00:00:00"}