{"id":"https://openalex.org/W4289175962","doi":"https://doi.org/10.1142/s1793962323500307","title":"A hybrid model for predicting academic performance of engineering undergraduates","display_name":"A hybrid model for predicting academic performance of engineering undergraduates","publication_year":2022,"publication_date":"2022-08-01","ids":{"openalex":"https://openalex.org/W4289175962","doi":"https://doi.org/10.1142/s1793962323500307"},"language":"en","primary_location":{"id":"doi:10.1142/s1793962323500307","is_oa":false,"landing_page_url":"https://doi.org/10.1142/s1793962323500307","pdf_url":null,"source":{"id":"https://openalex.org/S107361000","display_name":"Advances in Complex Systems","issn_l":"0219-5259","issn":["0219-5259","1793-6802","1793-9615","1793-9623"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319815","host_organization_name":"World Scientific","host_organization_lineage":["https://openalex.org/P4310319815"],"host_organization_lineage_names":["World Scientific"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"International Journal of Modeling, Simulation, and Scientific Computing","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/A5014760338","display_name":"Ke Niu","orcid":"https://orcid.org/0000-0003-1004-3613"},"institutions":[{"id":"https://openalex.org/I78675632","display_name":"Beijing Information Science & Technology University","ror":"https://ror.org/04xnqep60","country_code":"CN","type":"education","lineage":["https://openalex.org/I78675632"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Ke Niu","raw_affiliation_strings":["Computer School, Beijing Information Science and Technology University, Beijing, P. R. China"],"affiliations":[{"raw_affiliation_string":"Computer School, Beijing Information Science and Technology University, Beijing, P. R. China","institution_ids":["https://openalex.org/I78675632"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5113886238","display_name":"Baoting Jia","orcid":null},"institutions":[{"id":"https://openalex.org/I78675632","display_name":"Beijing Information Science & Technology University","ror":"https://ror.org/04xnqep60","country_code":"CN","type":"education","lineage":["https://openalex.org/I78675632"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"BaoTing Jia","raw_affiliation_strings":["Computer School, Beijing Information Science and Technology University, Beijing, P. R. China"],"affiliations":[{"raw_affiliation_string":"Computer School, Beijing Information Science and Technology University, Beijing, P. R. China","institution_ids":["https://openalex.org/I78675632"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101924581","display_name":"Yuhang Zhou","orcid":"https://orcid.org/0000-0002-9221-3331"},"institutions":[{"id":"https://openalex.org/I78675632","display_name":"Beijing Information Science & Technology University","ror":"https://ror.org/04xnqep60","country_code":"CN","type":"education","lineage":["https://openalex.org/I78675632"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"YuHang Zhou","raw_affiliation_strings":["Computer School, Beijing Information Science and Technology University, Beijing, P. R. China"],"affiliations":[{"raw_affiliation_string":"Computer School, Beijing Information Science and Technology University, Beijing, P. R. China","institution_ids":["https://openalex.org/I78675632"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5089152623","display_name":"Guoqiang Lu","orcid":"https://orcid.org/0000-0002-5062-4132"},"institutions":[{"id":"https://openalex.org/I78675632","display_name":"Beijing Information Science & Technology University","ror":"https://ror.org/04xnqep60","country_code":"CN","type":"education","lineage":["https://openalex.org/I78675632"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"GuoQiang Lu","raw_affiliation_strings":["Computer School, Beijing Information Science and Technology University, Beijing, P. R. China"],"affiliations":[{"raw_affiliation_string":"Computer School, Beijing Information Science and Technology University, Beijing, P. R. China","institution_ids":["https://openalex.org/I78675632"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5014760338"],"corresponding_institution_ids":["https://openalex.org/I78675632"],"apc_list":null,"apc_paid":null,"fwci":1.2637,"has_fulltext":false,"cited_by_count":6,"citation_normalized_percentile":{"value":0.8460257,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":97},"biblio":{"volume":"14","issue":"02","first_page":null,"last_page":null},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11122","display_name":"Online Learning and Analytics","score":0.9979000091552734,"subfield":{"id":"https://openalex.org/subfields/1706","display_name":"Computer Science Applications"},"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/T11122","display_name":"Online Learning and Analytics","score":0.9979000091552734,"subfield":{"id":"https://openalex.org/subfields/1706","display_name":"Computer Science Applications"},"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/T11652","display_name":"Imbalanced Data Classification Techniques","score":0.9818000197410583,"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/T11396","display_name":"Artificial Intelligence in Healthcare","score":0.9591000080108643,"subfield":{"id":"https://openalex.org/subfields/3605","display_name":"Health Information Management"},"field":{"id":"https://openalex.org/fields/36","display_name":"Health Professions"},"domain":{"id":"https://openalex.org/domains/4","display_name":"Health Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/naive-bayes-classifier","display_name":"Naive Bayes classifier","score":0.7765347361564636},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.6875805854797363},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6801402568817139},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6566061973571777},{"id":"https://openalex.org/keywords/performance-prediction","display_name":"Performance prediction","score":0.6268001198768616},{"id":"https://openalex.org/keywords/set","display_name":"Set (abstract data type)","score":0.47973719239234924},{"id":"https://openalex.org/keywords/classifier","display_name":"Classifier (UML)","score":0.4716809391975403},{"id":"https://openalex.org/keywords/bayes-theorem","display_name":"Bayes' theorem","score":0.46944472193717957},{"id":"https://openalex.org/keywords/radial-basis-function","display_name":"Radial basis function","score":0.4615137577056885},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.41614261269569397},{"id":"https://openalex.org/keywords/data-set","display_name":"Data set","score":0.41613149642944336},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.37931060791015625},{"id":"https://openalex.org/keywords/support-vector-machine","display_name":"Support vector machine","score":0.363175630569458},{"id":"https://openalex.org/keywords/simulation","display_name":"Simulation","score":0.12078210711479187},{"id":"https://openalex.org/keywords/bayesian-probability","display_name":"Bayesian probability","score":0.10587531328201294}],"concepts":[{"id":"https://openalex.org/C52001869","wikidata":"https://www.wikidata.org/wiki/Q812530","display_name":"Naive Bayes classifier","level":3,"score":0.7765347361564636},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.6875805854797363},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6801402568817139},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6566061973571777},{"id":"https://openalex.org/C2777115002","wikidata":"https://www.wikidata.org/wiki/Q7168246","display_name":"Performance prediction","level":2,"score":0.6268001198768616},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.47973719239234924},{"id":"https://openalex.org/C95623464","wikidata":"https://www.wikidata.org/wiki/Q1096149","display_name":"Classifier (UML)","level":2,"score":0.4716809391975403},{"id":"https://openalex.org/C207201462","wikidata":"https://www.wikidata.org/wiki/Q182505","display_name":"Bayes' theorem","level":3,"score":0.46944472193717957},{"id":"https://openalex.org/C98856871","wikidata":"https://www.wikidata.org/wiki/Q1588488","display_name":"Radial basis function","level":3,"score":0.4615137577056885},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.41614261269569397},{"id":"https://openalex.org/C58489278","wikidata":"https://www.wikidata.org/wiki/Q1172284","display_name":"Data set","level":2,"score":0.41613149642944336},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.37931060791015625},{"id":"https://openalex.org/C12267149","wikidata":"https://www.wikidata.org/wiki/Q282453","display_name":"Support vector machine","level":2,"score":0.363175630569458},{"id":"https://openalex.org/C44154836","wikidata":"https://www.wikidata.org/wiki/Q45045","display_name":"Simulation","level":1,"score":0.12078210711479187},{"id":"https://openalex.org/C107673813","wikidata":"https://www.wikidata.org/wiki/Q812534","display_name":"Bayesian probability","level":2,"score":0.10587531328201294},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1142/s1793962323500307","is_oa":false,"landing_page_url":"https://doi.org/10.1142/s1793962323500307","pdf_url":null,"source":{"id":"https://openalex.org/S107361000","display_name":"Advances in Complex Systems","issn_l":"0219-5259","issn":["0219-5259","1793-6802","1793-9615","1793-9623"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319815","host_organization_name":"World Scientific","host_organization_lineage":["https://openalex.org/P4310319815"],"host_organization_lineage_names":["World Scientific"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"International Journal of Modeling, Simulation, and Scientific Computing","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Quality Education","id":"https://metadata.un.org/sdg/4","score":0.5899999737739563}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":29,"referenced_works":["https://openalex.org/W1968295086","https://openalex.org/W2027283610","https://openalex.org/W2069992838","https://openalex.org/W2091007025","https://openalex.org/W2123504579","https://openalex.org/W2222888818","https://openalex.org/W2304692780","https://openalex.org/W2530106549","https://openalex.org/W2551429935","https://openalex.org/W2572242934","https://openalex.org/W2602821935","https://openalex.org/W2605296821","https://openalex.org/W2727650337","https://openalex.org/W2784169908","https://openalex.org/W2800788706","https://openalex.org/W2900420400","https://openalex.org/W2902943529","https://openalex.org/W2911978659","https://openalex.org/W2950527344","https://openalex.org/W2958616689","https://openalex.org/W2961070998","https://openalex.org/W2962970583","https://openalex.org/W2966800547","https://openalex.org/W2981531455","https://openalex.org/W2988618487","https://openalex.org/W3005533686","https://openalex.org/W3007847158","https://openalex.org/W3018999968","https://openalex.org/W4244089844"],"related_works":["https://openalex.org/W2394466068","https://openalex.org/W1987683558","https://openalex.org/W2726838704","https://openalex.org/W2096715552","https://openalex.org/W2133420660","https://openalex.org/W1794182708","https://openalex.org/W2537862391","https://openalex.org/W2417174640","https://openalex.org/W3006417263","https://openalex.org/W2067595037"],"abstract_inverted_index":{"Predicting":[0],"engineering":[1,42,170],"students\u2019":[2,16,43,103,171],"academic":[3,44,104,128,172],"performance":[4,45,129,173],"is":[5,57,78,123,142],"crucial":[6],"for":[7,150],"teachers":[8],"to":[9,14,19,40,71,80,101,125,144,164],"implement":[10],"teaching":[11],"interventions.":[12],"How":[13],"use":[15],"behavior":[17],"records":[18],"predict":[20,41,102,126],"grades":[21],"during":[22],"school":[23],"has":[24,84],"attracted":[25],"extensive":[26],"attention":[27],"from":[28,174],"researchers.":[29],"Various":[30],"machine":[31],"learning":[32,48],"methods":[33],"have":[34],"been":[35],"proposed":[36,158],"by":[37],"previous":[38,147],"researchers":[39,60],"through":[46],"their":[47],"records.":[49],"However,":[50],"one":[51],"of":[52,64,67,120,130,139,154],"the":[53,62,95,127,137,146,152,155,165,169,178],"major":[54],"challenges":[55],"now":[56],"that":[58],"many":[59],"ignore":[61],"problem":[63],"reduced":[65],"accuracy":[66,153],"prediction":[68,99,134,148,160],"models":[69],"due":[70],"imbalanced":[72],"data.":[73],"Simultaneously,":[74],"a":[75,175],"single":[76],"classifier":[77],"susceptible":[79],"data":[81,166,182],"changes":[82],"and":[83,114,132,177],"an":[85],"unstable":[86],"classification":[87],"performance.":[88],"To":[89],"this":[90,92],"end,":[91],"paper":[93],"proposes":[94],"RBF-Naive":[96],"Bayes":[97,116,141],"(RBFNB)":[98],"model":[100,161],"performance,":[105],"which":[106],"integrates":[107],"Radial":[108],"Basis":[109],"Function":[110],"(RBF)":[111],"Network":[112,122],"algorithm":[113],"Naive":[115,140],"algorithm.":[117],"The":[118,157],"method":[119,138],"RBF":[121],"applied":[124,163],"students":[131],"generate":[133],"results.":[135],"Then,":[136],"adopted":[143],"correct":[145],"results":[149],"improving":[151],"prediction.":[156],"RBFNB":[159],"was":[162],"set":[167],"about":[168],"university":[176],"Kalboard":[179],"360":[180],"public":[181],"set,":[183],"respectively.":[184]},"counts_by_year":[{"year":2025,"cited_by_count":3},{"year":2024,"cited_by_count":1},{"year":2023,"cited_by_count":2}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}