{"id":"https://openalex.org/W3176452618","doi":"https://doi.org/10.3390/e23070812","title":"A Novel Method to Determine Basic Probability Assignment Based on Adaboost and Its Application in Classification","display_name":"A Novel Method to Determine Basic Probability Assignment Based on Adaboost and Its Application in Classification","publication_year":2021,"publication_date":"2021-06-25","ids":{"openalex":"https://openalex.org/W3176452618","doi":"https://doi.org/10.3390/e23070812","mag":"3176452618","pmid":"https://pubmed.ncbi.nlm.nih.gov/34202212"},"language":"en","primary_location":{"id":"doi:10.3390/e23070812","is_oa":true,"landing_page_url":"https://doi.org/10.3390/e23070812","pdf_url":"https://www.mdpi.com/1099-4300/23/7/812/pdf?version=1624865590","source":{"id":"https://openalex.org/S195231649","display_name":"Entropy","issn_l":"1099-4300","issn":["1099-4300"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310310987","host_organization_name":"Multidisciplinary Digital Publishing Institute","host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Entropy","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj","pubmed"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://www.mdpi.com/1099-4300/23/7/812/pdf?version=1624865590","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5070458793","display_name":"Wei Fu","orcid":"https://orcid.org/0000-0001-5476-6448"},"institutions":[{"id":"https://openalex.org/I55022517","display_name":"Heilongjiang University","ror":"https://ror.org/04zyhq975","country_code":"CN","type":"education","lineage":["https://openalex.org/I55022517"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Wei Fu","raw_affiliation_strings":["Department of Automation, Heilongjiang University, Harbin 150080, China"],"affiliations":[{"raw_affiliation_string":"Department of Automation, Heilongjiang University, Harbin 150080, China","institution_ids":["https://openalex.org/I55022517"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5006758379","display_name":"Shuang Yu","orcid":"https://orcid.org/0000-0002-4022-6819"},"institutions":[{"id":"https://openalex.org/I55022517","display_name":"Heilongjiang University","ror":"https://ror.org/04zyhq975","country_code":"CN","type":"education","lineage":["https://openalex.org/I55022517"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Shuang Yu","raw_affiliation_strings":["Department of Automation, Heilongjiang University, Harbin 150080, China"],"affiliations":[{"raw_affiliation_string":"Department of Automation, Heilongjiang University, Harbin 150080, China","institution_ids":["https://openalex.org/I55022517"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100327833","display_name":"Xin Wang","orcid":"https://orcid.org/0000-0001-7955-2884"},"institutions":[{"id":"https://openalex.org/I55022517","display_name":"Heilongjiang University","ror":"https://ror.org/04zyhq975","country_code":"CN","type":"education","lineage":["https://openalex.org/I55022517"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Xin Wang","raw_affiliation_strings":["Department of Automation, Heilongjiang University, Harbin 150080, China","Key Laboratory of Information Fusion Estimation and Detection in Heilongjiang Province, Harbin 150080, China"],"affiliations":[{"raw_affiliation_string":"Department of Automation, Heilongjiang University, Harbin 150080, China","institution_ids":["https://openalex.org/I55022517"]},{"raw_affiliation_string":"Key Laboratory of Information Fusion Estimation and Detection in Heilongjiang Province, Harbin 150080, China","institution_ids":[]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5100327833"],"corresponding_institution_ids":["https://openalex.org/I55022517"],"apc_list":{"value":2000,"currency":"CHF","value_usd":2165},"apc_paid":{"value":2000,"currency":"CHF","value_usd":2165},"fwci":1.2599,"has_fulltext":false,"cited_by_count":14,"citation_normalized_percentile":{"value":0.83615294,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":97,"max":99},"biblio":{"volume":"23","issue":"7","first_page":"812","last_page":"812"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12535","display_name":"Machine Learning and Data Classification","score":0.9293000102043152,"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"}},"topics":[{"id":"https://openalex.org/T12535","display_name":"Machine Learning and Data Classification","score":0.9293000102043152,"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"}},{"id":"https://openalex.org/T11063","display_name":"Rough Sets and Fuzzy Logic","score":0.9248999953269958,"subfield":{"id":"https://openalex.org/subfields/1703","display_name":"Computational Theory and Mathematics"},"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/T13832","display_name":"Advanced Decision-Making Techniques","score":0.9056000113487244,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/adaboost","display_name":"AdaBoost","score":0.8025417923927307},{"id":"https://openalex.org/keywords/intersection","display_name":"Intersection (aeronautics)","score":0.7187021970748901},{"id":"https://openalex.org/keywords/singleton","display_name":"Singleton","score":0.6334080696105957},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6022930145263672},{"id":"https://openalex.org/keywords/proposition","display_name":"Proposition","score":0.5927572846412659},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5398650765419006},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.5155805945396423},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.4424739480018616},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.4046558737754822},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.3916740417480469},{"id":"https://openalex.org/keywords/support-vector-machine","display_name":"Support vector machine","score":0.09919935464859009}],"concepts":[{"id":"https://openalex.org/C141404830","wikidata":"https://www.wikidata.org/wiki/Q2823869","display_name":"AdaBoost","level":3,"score":0.8025417923927307},{"id":"https://openalex.org/C64543145","wikidata":"https://www.wikidata.org/wiki/Q162942","display_name":"Intersection (aeronautics)","level":2,"score":0.7187021970748901},{"id":"https://openalex.org/C117354338","wikidata":"https://www.wikidata.org/wiki/Q1165112","display_name":"Singleton","level":3,"score":0.6334080696105957},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6022930145263672},{"id":"https://openalex.org/C2777152325","wikidata":"https://www.wikidata.org/wiki/Q108163","display_name":"Proposition","level":2,"score":0.5927572846412659},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5398650765419006},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.5155805945396423},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.4424739480018616},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.4046558737754822},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.3916740417480469},{"id":"https://openalex.org/C12267149","wikidata":"https://www.wikidata.org/wiki/Q282453","display_name":"Support vector machine","level":2,"score":0.09919935464859009},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.0},{"id":"https://openalex.org/C146978453","wikidata":"https://www.wikidata.org/wiki/Q3798668","display_name":"Aerospace engineering","level":1,"score":0.0},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0},{"id":"https://openalex.org/C111472728","wikidata":"https://www.wikidata.org/wiki/Q9471","display_name":"Epistemology","level":1,"score":0.0},{"id":"https://openalex.org/C54355233","wikidata":"https://www.wikidata.org/wiki/Q7162","display_name":"Genetics","level":1,"score":0.0},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.0},{"id":"https://openalex.org/C2779234561","wikidata":"https://www.wikidata.org/wiki/Q11995","display_name":"Pregnancy","level":2,"score":0.0}],"mesh":[],"locations_count":5,"locations":[{"id":"doi:10.3390/e23070812","is_oa":true,"landing_page_url":"https://doi.org/10.3390/e23070812","pdf_url":"https://www.mdpi.com/1099-4300/23/7/812/pdf?version=1624865590","source":{"id":"https://openalex.org/S195231649","display_name":"Entropy","issn_l":"1099-4300","issn":["1099-4300"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310310987","host_organization_name":"Multidisciplinary Digital Publishing Institute","host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Entropy","raw_type":"journal-article"},{"id":"pmid:34202212","is_oa":false,"landing_page_url":"https://pubmed.ncbi.nlm.nih.gov/34202212","pdf_url":null,"source":{"id":"https://openalex.org/S4306525036","display_name":"PubMed","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I1299303238","host_organization_name":"National Institutes of Health","host_organization_lineage":["https://openalex.org/I1299303238"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Entropy (Basel, Switzerland)","raw_type":null},{"id":"pmh:oai:doaj.org/article:f52e3cc9604c4d38b52c4d3e58aa48ea","is_oa":true,"landing_page_url":"https://doaj.org/article/f52e3cc9604c4d38b52c4d3e58aa48ea","pdf_url":null,"source":{"id":"https://openalex.org/S112646816","display_name":"SHILAP Revista de lepidopterolog\u00eda","issn_l":"0300-5267","issn":["0300-5267","2340-4078"],"is_oa":true,"is_in_doaj":true,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"journal"},"license":"cc-by-sa","license_id":"https://openalex.org/licenses/cc-by-sa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Entropy, Vol 23, Iss 7, p 812 (2021)","raw_type":"article"},{"id":"pmh:oai:mdpi.com:/1099-4300/23/7/812/","is_oa":true,"landing_page_url":"https://dx.doi.org/10.3390/e23070812","pdf_url":null,"source":{"id":"https://openalex.org/S4306400947","display_name":"MDPI (MDPI AG)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I4210097602","host_organization_name":"Multidisciplinary Digital Publishing Institute (Switzerland)","host_organization_lineage":["https://openalex.org/I4210097602"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Entropy; Volume 23; Issue 7; Pages: 812","raw_type":"Text"},{"id":"pmh:oai:pubmedcentral.nih.gov:8305997","is_oa":true,"landing_page_url":"https://www.ncbi.nlm.nih.gov/pmc/articles/8305997","pdf_url":null,"source":{"id":"https://openalex.org/S2764455111","display_name":"PubMed Central","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I1299303238","host_organization_name":"National Institutes of Health","host_organization_lineage":["https://openalex.org/I1299303238"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Entropy (Basel)","raw_type":"Text"}],"best_oa_location":{"id":"doi:10.3390/e23070812","is_oa":true,"landing_page_url":"https://doi.org/10.3390/e23070812","pdf_url":"https://www.mdpi.com/1099-4300/23/7/812/pdf?version=1624865590","source":{"id":"https://openalex.org/S195231649","display_name":"Entropy","issn_l":"1099-4300","issn":["1099-4300"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310310987","host_organization_name":"Multidisciplinary Digital Publishing Institute","host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Entropy","raw_type":"journal-article"},"sustainable_development_goals":[{"display_name":"Peace, Justice and strong institutions","id":"https://metadata.un.org/sdg/16","score":0.6899999976158142}],"awards":[],"funders":[],"has_content":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W3176452618.pdf","grobid_xml":"https://content.openalex.org/works/W3176452618.grobid-xml"},"referenced_works_count":41,"referenced_works":["https://openalex.org/W2078410661","https://openalex.org/W2360194595","https://openalex.org/W2396175900","https://openalex.org/W2567563454","https://openalex.org/W2753290709","https://openalex.org/W2773903122","https://openalex.org/W2800093701","https://openalex.org/W2892131400","https://openalex.org/W2897380024","https://openalex.org/W2898331460","https://openalex.org/W2911780540","https://openalex.org/W2940445547","https://openalex.org/W2949754992","https://openalex.org/W2952138401","https://openalex.org/W2967850353","https://openalex.org/W2968862935","https://openalex.org/W2980328777","https://openalex.org/W2993958139","https://openalex.org/W2996089053","https://openalex.org/W2996251405","https://openalex.org/W2997080176","https://openalex.org/W2997496257","https://openalex.org/W2999193556","https://openalex.org/W2999859167","https://openalex.org/W3007999534","https://openalex.org/W3010884073","https://openalex.org/W3016013196","https://openalex.org/W3017365251","https://openalex.org/W3019762726","https://openalex.org/W3023644055","https://openalex.org/W3034792605","https://openalex.org/W3040765297","https://openalex.org/W3083814148","https://openalex.org/W3092168368","https://openalex.org/W3098861818","https://openalex.org/W3100152026","https://openalex.org/W3128828844","https://openalex.org/W3130713876","https://openalex.org/W3155913194","https://openalex.org/W6754658680","https://openalex.org/W6785291120"],"related_works":["https://openalex.org/W747331120","https://openalex.org/W2351588585","https://openalex.org/W4233660055","https://openalex.org/W2076370897","https://openalex.org/W2906951486","https://openalex.org/W3125437892","https://openalex.org/W2224172171","https://openalex.org/W1965730239","https://openalex.org/W2052181983","https://openalex.org/W4283313480"],"abstract_inverted_index":{"In":[0],"the":[1,8,17,28,64,67,71,84,91,95,104,108,130,135,138,142,149,155,161,164,170,178,184],"framework":[2],"of":[3,7,66,73,83,94,103,107,127,186],"evidence":[4],"theory,":[5],"one":[6],"open":[9],"and":[10,148,175,177],"crucial":[11],"issues":[12],"is":[13,23,31,60,87,111,114,146,152,158,173],"how":[14],"to":[15,26,50,62,133],"determine":[16,63],"basic":[18],"probability":[19],"assignment":[20],"(BPA),":[21],"which":[22,59,113],"directly":[24],"related":[25],"whether":[27],"decision":[29],"result":[30],"correct.":[32],"This":[33],"paper":[34],"proposes":[35],"a":[36],"novel":[37],"method":[38,46,132,172,180],"for":[39,55,78,117],"obtaining":[40],"BPA":[41,65,82],"based":[42],"on":[43],"Adaboost.":[44],"The":[45,81,100],"uses":[47],"training":[48,156],"data":[49],"generate":[51],"multiple":[52],"strong":[53],"classifiers":[54],"each":[56],"attribute":[57],"model,":[58],"used":[61],"singleton":[68,96],"proposition":[69,86],"since":[70],"weights":[72],"classification":[74,150],"provide":[75],"necessary":[76],"information":[77],"fundamental":[79],"hypotheses.":[80],"composite":[85],"quantified":[88],"by":[89,124],"calculating":[90],"area":[92,105],"ratio":[93,106],"proposition's":[97],"intersection":[98,109],"region.":[99],"recursive":[101],"formula":[102],"region":[110],"proposed,":[112],"very":[115],"useful":[116],"computer":[118],"calculation.":[119],"Finally,":[120],"BPAs":[121],"are":[122],"combined":[123],"Dempster's":[125],"rule":[126],"combination.":[128],"Using":[129],"proposed":[131,171,179],"classify":[134],"Iris":[136],"dataset,":[137],"experiment":[139,165],"concludes":[140],"that":[141,169],"total":[143],"recognition":[144],"rate":[145],"96.53%":[147],"accuracy":[151],"90%":[153],"when":[154],"percentage":[157],"10%.":[159],"For":[160],"other":[162],"datasets,":[163],"results":[166],"also":[167],"show":[168],"reasonable":[174],"effective,":[176],"performs":[181],"well":[182],"in":[183],"case":[185],"insufficient":[187],"samples.":[188]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":4},{"year":2024,"cited_by_count":5},{"year":2023,"cited_by_count":4}],"updated_date":"2026-03-20T23:20:44.827607","created_date":"2025-10-10T00:00:00"}
