{"id":"https://openalex.org/W2134869276","doi":"https://doi.org/10.1109/indin.2009.5195799","title":"Risk support vector machine for predicting the trend of enterprises development","display_name":"Risk support vector machine for predicting the trend of enterprises development","publication_year":2009,"publication_date":"2009-06-01","ids":{"openalex":"https://openalex.org/W2134869276","doi":"https://doi.org/10.1109/indin.2009.5195799","mag":"2134869276"},"language":"en","primary_location":{"id":"doi:10.1109/indin.2009.5195799","is_oa":false,"landing_page_url":"https://doi.org/10.1109/indin.2009.5195799","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2009 7th IEEE International Conference on Industrial Informatics","raw_type":"proceedings-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/A5001230438","display_name":"Wenliang Hu","orcid":null},"institutions":[{"id":"https://openalex.org/I82880672","display_name":"Beihang University","ror":"https://ror.org/00wk2mp56","country_code":"CN","type":"education","lineage":["https://openalex.org/I82880672"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Wenliang Hu","raw_affiliation_strings":["Department of Economy Management, Beihang University, Beijing, China","Department of Economy Management, Beihang University, Beijing, 100191, China"],"affiliations":[{"raw_affiliation_string":"Department of Economy Management, Beihang University, Beijing, China","institution_ids":["https://openalex.org/I82880672"]},{"raw_affiliation_string":"Department of Economy Management, Beihang University, Beijing, 100191, China","institution_ids":["https://openalex.org/I82880672"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5057451811","display_name":"Huiwen Wang","orcid":"https://orcid.org/0000-0002-1038-4349"},"institutions":[{"id":"https://openalex.org/I82880672","display_name":"Beihang University","ror":"https://ror.org/00wk2mp56","country_code":"CN","type":"education","lineage":["https://openalex.org/I82880672"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Huiwen Wang","raw_affiliation_strings":["Department of Economy Management, Beihang University, Beijing, China","Department of Economy Management, Beihang University, Beijing, 100191, China"],"affiliations":[{"raw_affiliation_string":"Department of Economy Management, Beihang University, Beijing, China","institution_ids":["https://openalex.org/I82880672"]},{"raw_affiliation_string":"Department of Economy Management, Beihang University, Beijing, 100191, China","institution_ids":["https://openalex.org/I82880672"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5001230438"],"corresponding_institution_ids":["https://openalex.org/I82880672"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.14051658,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"12","issue":null,"first_page":"177","last_page":"181"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10640","display_name":"Spectroscopy and Chemometric Analyses","score":0.9921000003814697,"subfield":{"id":"https://openalex.org/subfields/1602","display_name":"Analytical Chemistry"},"field":{"id":"https://openalex.org/fields/16","display_name":"Chemistry"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T10640","display_name":"Spectroscopy and Chemometric Analyses","score":0.9921000003814697,"subfield":{"id":"https://openalex.org/subfields/1602","display_name":"Analytical Chemistry"},"field":{"id":"https://openalex.org/fields/16","display_name":"Chemistry"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10876","display_name":"Fault Detection and Control Systems","score":0.9689000248908997,"subfield":{"id":"https://openalex.org/subfields/2207","display_name":"Control and Systems Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T14249","display_name":"Water Quality Monitoring and Analysis","score":0.9672999978065491,"subfield":{"id":"https://openalex.org/subfields/2311","display_name":"Industrial and Manufacturing Engineering"},"field":{"id":"https://openalex.org/fields/23","display_name":"Environmental Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/statistic","display_name":"Statistic","score":0.7351567149162292},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6721566319465637},{"id":"https://openalex.org/keywords/support-vector-machine","display_name":"Support vector machine","score":0.6499401330947876},{"id":"https://openalex.org/keywords/kernel","display_name":"Kernel (algebra)","score":0.4555855393409729},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.43641185760498047},{"id":"https://openalex.org/keywords/disequilibrium","display_name":"Disequilibrium","score":0.43046319484710693},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.4240977466106415},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.4208696782588959},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.139802485704422},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.11321035027503967}],"concepts":[{"id":"https://openalex.org/C89128539","wikidata":"https://www.wikidata.org/wiki/Q1949963","display_name":"Statistic","level":2,"score":0.7351567149162292},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6721566319465637},{"id":"https://openalex.org/C12267149","wikidata":"https://www.wikidata.org/wiki/Q282453","display_name":"Support vector machine","level":2,"score":0.6499401330947876},{"id":"https://openalex.org/C74193536","wikidata":"https://www.wikidata.org/wiki/Q574844","display_name":"Kernel (algebra)","level":2,"score":0.4555855393409729},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.43641185760498047},{"id":"https://openalex.org/C2778146401","wikidata":"https://www.wikidata.org/wiki/Q10916362","display_name":"Disequilibrium","level":2,"score":0.43046319484710693},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.4240977466106415},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4208696782588959},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.139802485704422},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.11321035027503967},{"id":"https://openalex.org/C71924100","wikidata":"https://www.wikidata.org/wiki/Q11190","display_name":"Medicine","level":0,"score":0.0},{"id":"https://openalex.org/C114614502","wikidata":"https://www.wikidata.org/wiki/Q76592","display_name":"Combinatorics","level":1,"score":0.0},{"id":"https://openalex.org/C118487528","wikidata":"https://www.wikidata.org/wiki/Q161437","display_name":"Ophthalmology","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/indin.2009.5195799","is_oa":false,"landing_page_url":"https://doi.org/10.1109/indin.2009.5195799","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2009 7th IEEE International Conference on Industrial Informatics","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Industry, innovation and infrastructure","score":0.6499999761581421,"id":"https://metadata.un.org/sdg/9"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":12,"referenced_works":["https://openalex.org/W1563088657","https://openalex.org/W1614098478","https://openalex.org/W2050378178","https://openalex.org/W2084649778","https://openalex.org/W2158863190","https://openalex.org/W2159059886","https://openalex.org/W2357087729","https://openalex.org/W2460724542","https://openalex.org/W2483389977","https://openalex.org/W3099514962","https://openalex.org/W4300546116","https://openalex.org/W6706337948"],"related_works":["https://openalex.org/W2037669709","https://openalex.org/W2374489386","https://openalex.org/W1966798854","https://openalex.org/W2486930869","https://openalex.org/W2361276589","https://openalex.org/W2385164240","https://openalex.org/W2389293267","https://openalex.org/W2375204466","https://openalex.org/W2900869704","https://openalex.org/W2389953037"],"abstract_inverted_index":{"Enterprises":[0],"development":[1],"trend":[2],"depends":[3],"on":[4,104],"many":[5],"factors":[6,15],"such":[7],"as":[8],"product,":[9],"distribution,":[10],"manpower":[11],"and":[12,18,33,45,67,93,108,159],"market.":[13,126],"These":[14],"are":[16],"interactive":[17],"coupling":[19],"in":[20,125],"statistic":[21,73],"data":[22,71],"that":[23,133],"makes":[24],"it":[25],"difficult":[26],"to":[27,40,51,61,82,120],"determine":[28],"which":[29,34],"enterprise":[30,111],"is":[31,49],"promising":[32,118],"one":[35],"should":[36],"transfer":[37],"type.":[38],"How":[39],"classify":[41,109],"the":[42,56,63,69,84,98,105,110,117,122,134,143,153],"enterprises":[43,119],"condition":[44],"predicate":[46],"their":[47],"future":[48],"urgent":[50],"solution.":[52],"This":[53],"paper":[54],"utilizes":[55],"inner":[57],"production":[58],"kernel":[59],"function":[60],"extract":[62],"useful":[64],"nonlinear":[65,146],"information":[66],"eliminate":[68],"redundant":[70],"from":[72],"information.":[74],"Then":[75],"present":[76],"a":[77],"risk":[78,99,135],"support":[79,136],"vector":[80,137],"machine":[81,138],"improve":[83],"classification":[85,156,164],"capability":[86],"of":[87,128,145],"multiple":[88],"variables":[89],"system":[90],"under":[91,157],"disequilibrium":[92],"limit":[94],"samples.":[95],"Through":[96],"introducing":[97],"probability,":[100],"we":[101],"can":[102,141,151],"focus":[103],"important":[106],"feature":[107,147],"with":[112,162],"high":[113,163],"precision,":[114],"then":[115],"invest":[116],"realize":[121,152],"high-tech":[123],"innovation":[124],"Application":[127],"Beihang":[129],"Discovery":[130],"Park":[131],"indicates":[132],"not":[139],"only":[140],"solve":[142],"problem":[144],"extraction":[148],"but":[149],"also":[150],"optimal":[154],"predication":[155],"unbalanced":[158],"small":[160],"samples":[161],"precision.":[165]},"counts_by_year":[],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}