{"id":"https://openalex.org/W4400368044","doi":"https://doi.org/10.1142/s0218213024400025","title":"Economic Data Forecasting Through Interval Data Analysis","display_name":"Economic Data Forecasting Through Interval Data Analysis","publication_year":2024,"publication_date":"2024-07-05","ids":{"openalex":"https://openalex.org/W4400368044","doi":"https://doi.org/10.1142/s0218213024400025"},"language":"en","primary_location":{"id":"doi:10.1142/s0218213024400025","is_oa":false,"landing_page_url":"https://doi.org/10.1142/s0218213024400025","pdf_url":null,"source":{"id":"https://openalex.org/S178780388","display_name":"International Journal of Artificial Intelligence Tools","issn_l":"0218-2130","issn":["0218-2130","1793-6349"],"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 on Artificial Intelligence Tools","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/A5107772053","display_name":"Yan Cheng","orcid":null},"institutions":[{"id":"https://openalex.org/I4210115456","display_name":"Chuzhou University","ror":"https://ror.org/037663q52","country_code":"CN","type":"education","lineage":["https://openalex.org/I4210115456"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yan Cheng","raw_affiliation_strings":["School of Economics and Management, Chuzhou University, Chuzhou 239000, P. R. China"],"raw_orcid":"https://orcid.org/0009-0006-7514-6372","affiliations":[{"raw_affiliation_string":"School of Economics and Management, Chuzhou University, Chuzhou 239000, P. R. China","institution_ids":["https://openalex.org/I4210115456"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5102813155","display_name":"Jinwen Su","orcid":"https://orcid.org/0009-0001-6566-2617"},"institutions":[{"id":"https://openalex.org/I4210115456","display_name":"Chuzhou University","ror":"https://ror.org/037663q52","country_code":"CN","type":"education","lineage":["https://openalex.org/I4210115456"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jinwen Su","raw_affiliation_strings":["College of Machinery and Electrical Engineering, Chuzhou University, Chuzhou 239000, P. R. China"],"raw_orcid":"https://orcid.org/0009-0001-6566-2617","affiliations":[{"raw_affiliation_string":"College of Machinery and Electrical Engineering, Chuzhou University, Chuzhou 239000, P. R. China","institution_ids":["https://openalex.org/I4210115456"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I4210115456"],"apc_list":null,"apc_paid":null,"fwci":0.7951,"has_fulltext":false,"cited_by_count":2,"citation_normalized_percentile":{"value":0.74084627,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":95},"biblio":{"volume":"33","issue":"07","first_page":null,"last_page":null},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11918","display_name":"Forecasting Techniques and Applications","score":0.6251000165939331,"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"}},"topics":[{"id":"https://openalex.org/T11918","display_name":"Forecasting Techniques and Applications","score":0.6251000165939331,"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/computer-science","display_name":"Computer science","score":0.8520261645317078},{"id":"https://openalex.org/keywords/interval","display_name":"Interval (graph theory)","score":0.4986748695373535},{"id":"https://openalex.org/keywords/interval-data","display_name":"Interval data","score":0.4848366975784302},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.4025256037712097}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8520261645317078},{"id":"https://openalex.org/C2778067643","wikidata":"https://www.wikidata.org/wiki/Q166507","display_name":"Interval (graph theory)","level":2,"score":0.4986748695373535},{"id":"https://openalex.org/C2983220686","wikidata":"https://www.wikidata.org/wiki/Q951437","display_name":"Interval data","level":3,"score":0.4848366975784302},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.4025256037712097},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.0},{"id":"https://openalex.org/C2780009758","wikidata":"https://www.wikidata.org/wiki/Q6804172","display_name":"Measure (data warehouse)","level":2,"score":0.0},{"id":"https://openalex.org/C114614502","wikidata":"https://www.wikidata.org/wiki/Q76592","display_name":"Combinatorics","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1142/s0218213024400025","is_oa":false,"landing_page_url":"https://doi.org/10.1142/s0218213024400025","pdf_url":null,"source":{"id":"https://openalex.org/S178780388","display_name":"International Journal of Artificial Intelligence Tools","issn_l":"0218-2130","issn":["0218-2130","1793-6349"],"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 on Artificial Intelligence Tools","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":44,"referenced_works":["https://openalex.org/W115732720","https://openalex.org/W134197611","https://openalex.org/W1988748730","https://openalex.org/W2050272421","https://openalex.org/W2122196572","https://openalex.org/W2125251038","https://openalex.org/W2260992041","https://openalex.org/W2268394201","https://openalex.org/W2270330859","https://openalex.org/W2283039974","https://openalex.org/W2545073277","https://openalex.org/W2606307670","https://openalex.org/W2747429511","https://openalex.org/W2774559076","https://openalex.org/W2781973163","https://openalex.org/W2891293381","https://openalex.org/W2902626052","https://openalex.org/W2911494597","https://openalex.org/W2942977997","https://openalex.org/W2973508239","https://openalex.org/W2990597424","https://openalex.org/W3000568686","https://openalex.org/W3045557651","https://openalex.org/W3047106696","https://openalex.org/W3093992164","https://openalex.org/W3103157245","https://openalex.org/W3110378470","https://openalex.org/W3125517020","https://openalex.org/W3156409915","https://openalex.org/W3170913408","https://openalex.org/W4210688171","https://openalex.org/W4220945596","https://openalex.org/W4221090139","https://openalex.org/W4224220755","https://openalex.org/W4226497757","https://openalex.org/W4280561011","https://openalex.org/W4293240845","https://openalex.org/W4304606463","https://openalex.org/W4318586138","https://openalex.org/W4320729752","https://openalex.org/W4384067368","https://openalex.org/W4388294554","https://openalex.org/W4388488561","https://openalex.org/W4392769733"],"related_works":["https://openalex.org/W115577841","https://openalex.org/W2032833645","https://openalex.org/W4256681807","https://openalex.org/W2338920004","https://openalex.org/W2232227265","https://openalex.org/W2045103335","https://openalex.org/W4232843823","https://openalex.org/W2205126926","https://openalex.org/W3139960064","https://openalex.org/W2624046717"],"abstract_inverted_index":{"As":[0],"an":[1],"important":[2],"reflection":[3],"of":[4,17,25,34,45,153,159,167,191],"the":[5,15,28,31,35,46,50,58,80,87,103,138,165,189],"national":[6],"economy":[7],"system,":[8],"stock":[9,36,38,59,76,81,127,162,169,196],"market":[10,186],"is":[11,61,97],"closely":[12],"related":[13],"to":[14,101,114,163],"development":[16],"a":[18,98,160],"country,":[19],"which":[20,64,108,171],"has":[21,41],"received":[22],"widespread":[23],"attention":[24],"researchers":[26],"in":[27,49,83,117,177],"economics.":[29],"With":[30],"daily":[32],"trading":[33],"market,":[37],"price":[39,60,82,88,128,149,152,170,197],"forecasting":[40,56,77],"gradually":[42],"been":[43],"one":[44],"common":[47],"concerns":[48],"economic":[51],"analysis.":[52],"Compared":[53,130],"with":[54,131],"traditional":[55,132],"task,":[57],"interval":[62,69],"data":[63,70,176],"can":[65,142],"be":[66,94],"handled":[67],"by":[68],"regression":[71,133,136,141,194],"or":[72,134],"multi-output":[73,123,135,139,192],"regression.":[74],"Previous":[75],"merely":[78],"considers":[79],"homogeneous":[84],"scenarios.":[85],"However,":[86],"distributions":[89],"from":[90],"different":[91,106],"stocks":[92,107,116,154],"may":[93,172],"heterogeneous.":[95],"It":[96],"challenging":[99],"task":[100],"analyze":[102],"relationship":[104],"between":[105],"follow":[109],"heterogeneous":[110,118],"distributions.":[111],"In":[112],"order":[113],"forecast":[115],"scenarios,":[119],"this":[120],"paper":[121],"introduces":[122],"transfer":[124,140,193],"learning":[125],"into":[126],"forecasting.":[129,198],"models,":[137],"predict":[143],"opening":[144],"price,":[145,147],"closing":[146],"highest":[148],"and":[150,155],"lowest":[151],"utilize":[156],"source":[157],"domain":[158],"known":[161,175],"enhance":[164],"prediction":[166],"target":[168],"have":[173],"limited":[174],"training":[178],"set.":[179],"The":[180],"experimental":[181],"results":[182],"on":[183],"four":[184],"public":[185],"indices":[187],"demonstrate":[188],"effectiveness":[190],"for":[195]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2024,"cited_by_count":1}],"updated_date":"2026-05-21T06:26:12.895304","created_date":"2025-10-10T00:00:00"}