{"id":"https://openalex.org/W4379196873","doi":"https://doi.org/10.3233/jifs-222879","title":"More accurate simulation for insurance data based on a modified SVM polynomial method1","display_name":"More accurate simulation for insurance data based on a modified SVM polynomial method1","publication_year":2023,"publication_date":"2023-05-30","ids":{"openalex":"https://openalex.org/W4379196873","doi":"https://doi.org/10.3233/jifs-222879"},"language":"en","primary_location":{"id":"doi:10.3233/jifs-222879","is_oa":false,"landing_page_url":"https://doi.org/10.3233/jifs-222879","pdf_url":null,"source":{"id":"https://openalex.org/S179157397","display_name":"Journal of Intelligent & Fuzzy Systems","issn_l":"1064-1246","issn":["1064-1246","1875-8967"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310318577","host_organization_name":"IOS Press","host_organization_lineage":["https://openalex.org/P4310318577"],"host_organization_lineage_names":["IOS Press"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Journal of Intelligent &amp; Fuzzy Systems","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/A5018634618","display_name":"Irfan Nurhidayat","orcid":"https://orcid.org/0000-0002-2655-949X"},"institutions":[{"id":"https://openalex.org/I91538806","display_name":"King Mongkut's Institute of Technology Ladkrabang","ror":"https://ror.org/055mf0v62","country_code":"TH","type":"education","lineage":["https://openalex.org/I91538806"]}],"countries":["TH"],"is_corresponding":false,"raw_author_name":"Irfan Nurhidayat","raw_affiliation_strings":["Department of Mathematics, School of Science, King Mongkut\u2019s Institute of Technology Ladkrabang, Bangkok, 10520, Thailand","Department of Mathematics, School of Science, King Mongkut's Institute of Technology Ladkrabang, Bangkok, 10520, Thailand"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Mathematics, School of Science, King Mongkut\u2019s Institute of Technology Ladkrabang, Bangkok, 10520, Thailand","institution_ids":["https://openalex.org/I91538806"]},{"raw_affiliation_string":"Department of Mathematics, School of Science, King Mongkut's Institute of Technology Ladkrabang, Bangkok, 10520, Thailand","institution_ids":["https://openalex.org/I91538806"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5075150232","display_name":"Busayamas Pimpunchat","orcid":"https://orcid.org/0000-0003-2550-7484"},"institutions":[{"id":"https://openalex.org/I91538806","display_name":"King Mongkut's Institute of Technology Ladkrabang","ror":"https://ror.org/055mf0v62","country_code":"TH","type":"education","lineage":["https://openalex.org/I91538806"]}],"countries":["TH"],"is_corresponding":true,"raw_author_name":"Busayamas Pimpunchat","raw_affiliation_strings":["Department of Mathematics, School of Science, King Mongkut\u2019s Institute of Technology Ladkrabang, Bangkok, 10520, Thailand","Department of Mathematics, School of Science, King Mongkut's Institute of Technology Ladkrabang, Bangkok, 10520, Thailand"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Mathematics, School of Science, King Mongkut\u2019s Institute of Technology Ladkrabang, Bangkok, 10520, Thailand","institution_ids":["https://openalex.org/I91538806"]},{"raw_affiliation_string":"Department of Mathematics, School of Science, King Mongkut's Institute of Technology Ladkrabang, Bangkok, 10520, Thailand","institution_ids":["https://openalex.org/I91538806"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5092077215","display_name":"Wiriyabhorn Klomsungcharoen","orcid":null},"institutions":[{"id":"https://openalex.org/I4210132654","display_name":"Valaya Alongkorn Rajabhat University","ror":"https://ror.org/04hp7kk26","country_code":"TH","type":"education","lineage":["https://openalex.org/I4210132654"]}],"countries":["TH"],"is_corresponding":false,"raw_author_name":"Wiriyabhorn Klomsungcharoen","raw_affiliation_strings":["Department of Applied Mathematics, Faculty of Science and Technology, Valaya Alongkorn Rajabhat University under the Royal Patronage, Pathum Thani, 13180, Thailand"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Applied Mathematics, Faculty of Science and Technology, Valaya Alongkorn Rajabhat University under the Royal Patronage, Pathum Thani, 13180, Thailand","institution_ids":["https://openalex.org/I4210132654"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5075150232"],"corresponding_institution_ids":["https://openalex.org/I91538806"],"apc_list":null,"apc_paid":null,"fwci":0.4759,"has_fulltext":false,"cited_by_count":3,"citation_normalized_percentile":{"value":0.67620353,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":96},"biblio":{"volume":"44","issue":"6","first_page":"9129","last_page":"9141"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11652","display_name":"Imbalanced Data Classification Techniques","score":0.9685999751091003,"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/T11652","display_name":"Imbalanced Data Classification Techniques","score":0.9685999751091003,"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/T11886","display_name":"Agricultural risk and resilience","score":0.9682000279426575,"subfield":{"id":"https://openalex.org/subfields/1111","display_name":"Soil Science"},"field":{"id":"https://openalex.org/fields/11","display_name":"Agricultural and Biological Sciences"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}},{"id":"https://openalex.org/T11413","display_name":"Risk and Portfolio Optimization","score":0.9433000087738037,"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/support-vector-machine","display_name":"Support vector machine","score":0.7926822900772095},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6701905727386475},{"id":"https://openalex.org/keywords/polynomial","display_name":"Polynomial","score":0.6370442509651184},{"id":"https://openalex.org/keywords/polynomial-and-rational-function-modeling","display_name":"Polynomial and rational function modeling","score":0.4524182677268982},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.44613319635391235},{"id":"https://openalex.org/keywords/smoothing","display_name":"Smoothing","score":0.4257740378379822},{"id":"https://openalex.org/keywords/mathematical-optimization","display_name":"Mathematical optimization","score":0.4117438793182373},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.3635610342025757},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.24678143858909607},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.23659393191337585}],"concepts":[{"id":"https://openalex.org/C12267149","wikidata":"https://www.wikidata.org/wiki/Q282453","display_name":"Support vector machine","level":2,"score":0.7926822900772095},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6701905727386475},{"id":"https://openalex.org/C90119067","wikidata":"https://www.wikidata.org/wiki/Q43260","display_name":"Polynomial","level":2,"score":0.6370442509651184},{"id":"https://openalex.org/C138029060","wikidata":"https://www.wikidata.org/wiki/Q7226633","display_name":"Polynomial and rational function modeling","level":3,"score":0.4524182677268982},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.44613319635391235},{"id":"https://openalex.org/C3770464","wikidata":"https://www.wikidata.org/wiki/Q775963","display_name":"Smoothing","level":2,"score":0.4257740378379822},{"id":"https://openalex.org/C126255220","wikidata":"https://www.wikidata.org/wiki/Q141495","display_name":"Mathematical optimization","level":1,"score":0.4117438793182373},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.3635610342025757},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.24678143858909607},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.23659393191337585},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.0},{"id":"https://openalex.org/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.3233/jifs-222879","is_oa":false,"landing_page_url":"https://doi.org/10.3233/jifs-222879","pdf_url":null,"source":{"id":"https://openalex.org/S179157397","display_name":"Journal of Intelligent & Fuzzy Systems","issn_l":"1064-1246","issn":["1064-1246","1875-8967"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310318577","host_organization_name":"IOS Press","host_organization_lineage":["https://openalex.org/P4310318577"],"host_organization_lineage_names":["IOS Press"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Journal of Intelligent &amp; Fuzzy Systems","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":40,"referenced_works":["https://openalex.org/W1609962231","https://openalex.org/W1919040799","https://openalex.org/W1994642659","https://openalex.org/W2006617902","https://openalex.org/W2011348115","https://openalex.org/W2033498061","https://openalex.org/W2067430497","https://openalex.org/W2078622638","https://openalex.org/W2081011933","https://openalex.org/W2084800543","https://openalex.org/W2097687553","https://openalex.org/W2130728435","https://openalex.org/W2149029960","https://openalex.org/W2149454052","https://openalex.org/W2150196286","https://openalex.org/W2158698691","https://openalex.org/W2328176404","https://openalex.org/W2340930132","https://openalex.org/W2782727044","https://openalex.org/W2792095633","https://openalex.org/W2806410959","https://openalex.org/W2811481730","https://openalex.org/W2899714726","https://openalex.org/W2936203654","https://openalex.org/W2985957070","https://openalex.org/W2997833216","https://openalex.org/W3008649177","https://openalex.org/W3024515706","https://openalex.org/W3091084910","https://openalex.org/W3147683293","https://openalex.org/W3169581362","https://openalex.org/W3197743078","https://openalex.org/W4214668831","https://openalex.org/W4281877133","https://openalex.org/W4286819902","https://openalex.org/W4297370948","https://openalex.org/W4308125153","https://openalex.org/W6671902145","https://openalex.org/W6764836623","https://openalex.org/W6792962671"],"related_works":["https://openalex.org/W2083214991","https://openalex.org/W2382515275","https://openalex.org/W2799377959","https://openalex.org/W2378881172","https://openalex.org/W1991218450","https://openalex.org/W2377808330","https://openalex.org/W2582856396","https://openalex.org/W2889181883","https://openalex.org/W2379041201","https://openalex.org/W2126405149"],"abstract_inverted_index":{"This":[0,198,221],"study":[1],"aims":[2],"to":[3,12,33,52,107,180,188,205],"present":[4],"the":[5,35,50,54,68,73,109,119,125,129,169,176,189,238],"modified":[6,22,55,74,110,137,170],"SVM":[7,23,56,61,76,111,138,171,191],"polynomial":[8,24,57,62,75,112,139,172,192],"method":[9,63,173],"in":[10,71,155],"order":[11],"evaluate":[13],"insurance":[14,151],"data.":[15,220,245],"The":[16,59,114],"research":[17,115],"methodology":[18],"discusses":[19],"classical":[20,60,135,190],"and":[21,29,97,128,136,185,229],"methods":[25,149],"by":[26,209],"R":[27,211],"programming,":[28],"uses":[30],"performance":[31,121],"profiles":[32,122,142],"create":[34],"most":[36],"preferable":[37],"methods.":[38,140],"It":[39,158],"offers":[40],"a":[41],"new":[42],"algorithm":[43,48,167,201],"called":[44],"an":[45,102,164],"accurate":[46,103,165,199,231],"evaluating":[47,104,166,200],"as":[49,67],"way":[51],"construct":[53],"method.":[58,77,113],"is":[64,195],"also":[65,117,153],"represented":[66],"main":[69],"idea":[70],"finding":[72],"Model":[78],"Performance":[79,141],"Evaluation":[80],"(MPE),":[81],"Receiver":[82],"Operating":[83],"Characteristics":[84],"(ROCs)":[85],"Curve,":[86],"Area":[87],"Under":[88],"Curve":[89],"(AUC),":[90],"partial":[91],"AUC":[92],"(pAUC),":[93],"smoothing,":[94],"confidence":[95],"intervals,":[96],"thresholds":[98],"are":[99],"further":[100],"named":[101],"algorithm,":[105],"employed":[106],"build":[108],"paper":[116],"presents":[118],"best":[120],"based":[123,146],"on":[124,147,168],"computing":[126,183],"time":[127,184],"number":[130],"of":[131,133],"iterations":[132,186],"both":[134,148],"show":[143],"numerical":[144],"comparisons":[145],"involving":[150],"data":[152,177,208,232],"displayed":[154],"this":[156],"paper.":[157],"can":[159,202,235],"be":[160,203],"concluded":[161],"that":[162,219,234],"applying":[163],"will":[174,224],"improve":[175],"accuracy":[178],"up":[179],"86%":[181],"via":[182],"compared":[187],"method,":[193],"which":[194],"only":[196],"79%.":[197],"applied":[204],"various":[206],"large-sized":[207],"utilizing":[210],"programming":[212],"with":[213,244],"changing":[214],"any":[215],"suitable":[216],"kernels":[217],"for":[218,227],"vital":[222],"discovery":[223],"offer":[225],"solutions":[226],"faster":[228],"more":[230],"analysis":[233],"benefit":[236],"researchers,":[237],"private":[239],"sector,":[240],"or":[241],"governments":[242],"struggling":[243]},"counts_by_year":[{"year":2025,"cited_by_count":2},{"year":2024,"cited_by_count":1}],"updated_date":"2026-05-21T06:26:12.895304","created_date":"2025-10-10T00:00:00"}
