{"id":"https://openalex.org/W4399254497","doi":"https://doi.org/10.1145/3656766.3656941","title":"Enterprise Credit Rating Model Based on Long and Short-Term Trend of Desensitized Power Load Data","display_name":"Enterprise Credit Rating Model Based on Long and Short-Term Trend of Desensitized Power Load Data","publication_year":2023,"publication_date":"2023-11-24","ids":{"openalex":"https://openalex.org/W4399254497","doi":"https://doi.org/10.1145/3656766.3656941"},"language":"en","primary_location":{"id":"doi:10.1145/3656766.3656941","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3656766.3656941","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2023 3rd International Conference on Big Data, Artificial Intelligence and Risk Management","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/A5054597820","display_name":"Yi Wu","orcid":"https://orcid.org/0000-0002-5913-2126"},"institutions":[{"id":"https://openalex.org/I4210126065","display_name":"Shanghai Electric (China)","ror":"https://ror.org/0314qy595","country_code":"CN","type":"company","lineage":["https://openalex.org/I4210126065"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Yi Wu","raw_affiliation_strings":["State Grid Shanghai Municipal Electric Power Company, China"],"affiliations":[{"raw_affiliation_string":"State Grid Shanghai Municipal Electric Power Company, China","institution_ids":["https://openalex.org/I4210126065"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5066577453","display_name":"Zenghui Xi","orcid":"https://orcid.org/0009-0009-4966-6851"},"institutions":[{"id":"https://openalex.org/I4210126065","display_name":"Shanghai Electric (China)","ror":"https://ror.org/0314qy595","country_code":"CN","type":"company","lineage":["https://openalex.org/I4210126065"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zenghui Xi","raw_affiliation_strings":["State Grid Shanghai Municipal Electric Power Company, China"],"affiliations":[{"raw_affiliation_string":"State Grid Shanghai Municipal Electric Power Company, China","institution_ids":["https://openalex.org/I4210126065"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5064983193","display_name":"Weibin Wang","orcid":"https://orcid.org/0009-0003-4523-3430"},"institutions":[{"id":"https://openalex.org/I4210126065","display_name":"Shanghai Electric (China)","ror":"https://ror.org/0314qy595","country_code":"CN","type":"company","lineage":["https://openalex.org/I4210126065"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Weibin Wang","raw_affiliation_strings":["State Grid Shanghai Municipal Electric Power Company, China"],"affiliations":[{"raw_affiliation_string":"State Grid Shanghai Municipal Electric Power Company, China","institution_ids":["https://openalex.org/I4210126065"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5064014953","display_name":"Qian Li","orcid":"https://orcid.org/0009-0001-6971-6571"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Qian Li","raw_affiliation_strings":["Shanghai Fudata Technology Co. Ltd, China"],"affiliations":[{"raw_affiliation_string":"Shanghai Fudata Technology Co. Ltd, China","institution_ids":[]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5054597820"],"corresponding_institution_ids":["https://openalex.org/I4210126065"],"apc_list":null,"apc_paid":null,"fwci":0.4872,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":{"value":0.73958375,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":91,"max":95},"biblio":{"volume":null,"issue":null,"first_page":"1060","last_page":"1064"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11653","display_name":"Financial Distress and Bankruptcy Prediction","score":0.8709999918937683,"subfield":{"id":"https://openalex.org/subfields/1402","display_name":"Accounting"},"field":{"id":"https://openalex.org/fields/14","display_name":"Business, Management and Accounting"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},"topics":[{"id":"https://openalex.org/T11653","display_name":"Financial Distress and Bankruptcy Prediction","score":0.8709999918937683,"subfield":{"id":"https://openalex.org/subfields/1402","display_name":"Accounting"},"field":{"id":"https://openalex.org/fields/14","display_name":"Business, Management and Accounting"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},{"id":"https://openalex.org/T11719","display_name":"Data Quality and Management","score":0.8141000270843506,"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/T14400","display_name":"Medical Coding and Health Information","score":0.8086000084877014,"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/computer-science","display_name":"Computer science","score":0.7216445803642273},{"id":"https://openalex.org/keywords/big-data","display_name":"Big data","score":0.6865798234939575},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.5686352252960205},{"id":"https://openalex.org/keywords/cluster-analysis","display_name":"Cluster analysis","score":0.4997842311859131},{"id":"https://openalex.org/keywords/data-set","display_name":"Data set","score":0.49481624364852905},{"id":"https://openalex.org/keywords/data-modeling","display_name":"Data modeling","score":0.47844198346138},{"id":"https://openalex.org/keywords/asset","display_name":"Asset (computer security)","score":0.4783982038497925},{"id":"https://openalex.org/keywords/construct","display_name":"Construct (python library)","score":0.45170605182647705},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.42512503266334534},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.4068569242954254},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.3870371878147125},{"id":"https://openalex.org/keywords/database","display_name":"Database","score":0.2192486822605133}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7216445803642273},{"id":"https://openalex.org/C75684735","wikidata":"https://www.wikidata.org/wiki/Q858810","display_name":"Big data","level":2,"score":0.6865798234939575},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.5686352252960205},{"id":"https://openalex.org/C73555534","wikidata":"https://www.wikidata.org/wiki/Q622825","display_name":"Cluster analysis","level":2,"score":0.4997842311859131},{"id":"https://openalex.org/C58489278","wikidata":"https://www.wikidata.org/wiki/Q1172284","display_name":"Data set","level":2,"score":0.49481624364852905},{"id":"https://openalex.org/C67186912","wikidata":"https://www.wikidata.org/wiki/Q367664","display_name":"Data modeling","level":2,"score":0.47844198346138},{"id":"https://openalex.org/C76178495","wikidata":"https://www.wikidata.org/wiki/Q4808784","display_name":"Asset (computer security)","level":2,"score":0.4783982038497925},{"id":"https://openalex.org/C2780801425","wikidata":"https://www.wikidata.org/wiki/Q5164392","display_name":"Construct (python library)","level":2,"score":0.45170605182647705},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.42512503266334534},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4068569242954254},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3870371878147125},{"id":"https://openalex.org/C77088390","wikidata":"https://www.wikidata.org/wiki/Q8513","display_name":"Database","level":1,"score":0.2192486822605133},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.0},{"id":"https://openalex.org/C38652104","wikidata":"https://www.wikidata.org/wiki/Q3510521","display_name":"Computer security","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3656766.3656941","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3656766.3656941","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2023 3rd International Conference on Big Data, Artificial Intelligence and Risk Management","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.47999998927116394,"display_name":"Decent work and economic growth","id":"https://metadata.un.org/sdg/8"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":19,"referenced_works":["https://openalex.org/W1550206324","https://openalex.org/W1566141574","https://openalex.org/W1673066967","https://openalex.org/W1994345439","https://openalex.org/W1995254696","https://openalex.org/W2005596732","https://openalex.org/W2029869759","https://openalex.org/W2124532504","https://openalex.org/W2205836349","https://openalex.org/W2250194349","https://openalex.org/W2761075141","https://openalex.org/W2897938727","https://openalex.org/W2922475392","https://openalex.org/W3098937120","https://openalex.org/W3175387598","https://openalex.org/W3182350536","https://openalex.org/W4224253356","https://openalex.org/W4237079720","https://openalex.org/W6713312025"],"related_works":["https://openalex.org/W2366107444","https://openalex.org/W4388145910","https://openalex.org/W4390608645","https://openalex.org/W2381570729","https://openalex.org/W1976205134","https://openalex.org/W4247566972","https://openalex.org/W4394895745","https://openalex.org/W4248336175","https://openalex.org/W2960264696","https://openalex.org/W3128438030"],"abstract_inverted_index":{"This":[0],"paper":[1,109],"explores":[2,39],"the":[3,18,26,29,40,49,58,61,64,108,174,177],"fusion":[4],"and":[5,11,38,54,67,78,123,135],"application":[6],"of":[7,20,32,42,51,63,113,145,161,176],"big":[8,96],"data":[9,22,34,45,68,71,163],"mining":[10,72,105],"artificial":[12],"intelligence":[13],"technology":[14],"to":[15,83,172],"delve":[16],"into":[17],"value":[19],"power":[21,33,44,65,95,114,162,179],"assets.":[23,46],"It":[24],"advances":[25],"research":[27],"on":[28,48,139,167],"business":[30,52],"model":[31,93],"in":[35],"enterprise":[36],"credit":[37,79,90,115,136,180],"feasibility":[41],"implementing":[43],"Based":[47],"exploration":[50],"models":[53],"existing":[55],"project":[56],"databases,":[57],"paper,":[59],"considering":[60],"characteristics":[62],"industry":[66],"foundation,":[69],"uses":[70],"methods,":[73,77],"label":[74,116],"system":[75,81],"construction":[76],"evaluation":[80],"methods":[82],"construct":[84],"an":[85],"attentional":[86,152],"convolution":[87,153],"neural":[88,154],"network-based":[89],"rating":[91],"(ACNNCR)":[92],"for":[94,151],"data.":[97,142],"Utilizing":[98],"clustering":[99],"algorithms,":[100,106],"expert":[101],"rules,":[102],"statistical":[103],"modelling,":[104],"etc.,":[107],"develops":[110],"a":[111,158],"set":[112],"models,":[117],"including":[118],"factual":[119],"labels,":[120,122,125],"rule-based":[121],"predictive":[124],"within":[126],"dimensions":[127],"such":[128],"as":[129],"user":[130,141],"attributes,":[131],"electricity":[132],"usage":[133],"characteristics,":[134],"features,":[137],"based":[138],"non-residential":[140],"A":[143],"total":[144],"185":[146],"features":[147],"are":[148],"successfully":[149],"established":[150],"network":[155],"model,":[156],"forming":[157],"new":[159],"type":[160],"asset.":[164],"Case":[165],"verification":[166],"real-life":[168],"datasets":[169],"is":[170],"used":[171],"validate":[173],"effectiveness":[175],"constructed":[178],"labels.":[181]},"counts_by_year":[{"year":2025,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}