{"id":"https://openalex.org/W3016056490","doi":"https://doi.org/10.1080/0952813x.2020.1744195","title":"Double-quantitative decision rough set over two universes and application to African swine fever decision-making","display_name":"Double-quantitative decision rough set over two universes and application to African swine fever decision-making","publication_year":2020,"publication_date":"2020-04-13","ids":{"openalex":"https://openalex.org/W3016056490","doi":"https://doi.org/10.1080/0952813x.2020.1744195","mag":"3016056490"},"language":"en","primary_location":{"id":"doi:10.1080/0952813x.2020.1744195","is_oa":true,"landing_page_url":"https://doi.org/10.1080/0952813x.2020.1744195","pdf_url":"https://www.tandfonline.com/doi/pdf/10.1080/0952813X.2020.1744195?needAccess=true","source":{"id":"https://openalex.org/S153467142","display_name":"Journal of Experimental & Theoretical Artificial Intelligence","issn_l":"0952-813X","issn":["0952-813X","1362-3079"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310320547","host_organization_name":"Taylor & Francis","host_organization_lineage":["https://openalex.org/P4310320547"],"host_organization_lineage_names":["Taylor & Francis"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Journal of Experimental &amp; Theoretical Artificial Intelligence","raw_type":"journal-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"bronze","oa_url":"https://www.tandfonline.com/doi/pdf/10.1080/0952813X.2020.1744195?needAccess=true","any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5000261720","display_name":"Xiaoyuan Hu","orcid":null},"institutions":[{"id":"https://openalex.org/I149594827","display_name":"Xidian University","ror":"https://ror.org/05s92vm98","country_code":"CN","type":"education","lineage":["https://openalex.org/I149594827"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xiaoyuan Hu","raw_affiliation_strings":["School of Economics and Management, Xidian University, Xi\u2019an, Shaanxi, China"],"affiliations":[{"raw_affiliation_string":"School of Economics and Management, Xidian University, Xi\u2019an, Shaanxi, China","institution_ids":["https://openalex.org/I149594827"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5037780781","display_name":"Bingzhen Sun","orcid":"https://orcid.org/0000-0002-5105-8291"},"institutions":[{"id":"https://openalex.org/I149594827","display_name":"Xidian University","ror":"https://ror.org/05s92vm98","country_code":"CN","type":"education","lineage":["https://openalex.org/I149594827"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Bingzhen Sun","raw_affiliation_strings":["School of Economics and Management, Xidian University, Xi\u2019an, Shaanxi, China"],"affiliations":[{"raw_affiliation_string":"School of Economics and Management, Xidian University, Xi\u2019an, Shaanxi, China","institution_ids":["https://openalex.org/I149594827"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100427905","display_name":"Ting Wang","orcid":"https://orcid.org/0000-0001-8545-1844"},"institutions":[{"id":"https://openalex.org/I149594827","display_name":"Xidian University","ror":"https://ror.org/05s92vm98","country_code":"CN","type":"education","lineage":["https://openalex.org/I149594827"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Ting Wang","raw_affiliation_strings":["School of Economics and Management, Xidian University, Xi\u2019an, Shaanxi, China"],"affiliations":[{"raw_affiliation_string":"School of Economics and Management, Xidian University, Xi\u2019an, Shaanxi, China","institution_ids":["https://openalex.org/I149594827"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5101443427","display_name":"Chao Jiang","orcid":"https://orcid.org/0000-0002-3929-6705"},"institutions":[{"id":"https://openalex.org/I4210107780","display_name":"Xi'an Medical University","ror":"https://ror.org/01fmc2233","country_code":"CN","type":"education","lineage":["https://openalex.org/I4210107780"]},{"id":"https://openalex.org/I4210101984","display_name":"Longhua Hospital Shanghai University of Traditional Chinese Medicine","ror":"https://ror.org/016yezh07","country_code":"CN","type":"healthcare","lineage":["https://openalex.org/I4210101984"]},{"id":"https://openalex.org/I4210098460","display_name":"Shanghai University of Traditional Chinese Medicine","ror":"https://ror.org/00z27jk27","country_code":"CN","type":"education","lineage":["https://openalex.org/I4210098460"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Chao Jiang","raw_affiliation_strings":["Department of Emergency, Longhua Hospital Shanghai University of Traditional Chinese Medicine, Shanghai, China","The Third Department of Neurology, The Second Affiliated Hospital of Xi\u2019an Medical University, Xi\u2019an, Shaanxi, China"],"affiliations":[{"raw_affiliation_string":"Department of Emergency, Longhua Hospital Shanghai University of Traditional Chinese Medicine, Shanghai, China","institution_ids":["https://openalex.org/I4210101984","https://openalex.org/I4210098460"]},{"raw_affiliation_string":"The Third Department of Neurology, The Second Affiliated Hospital of Xi\u2019an Medical University, Xi\u2019an, Shaanxi, China","institution_ids":["https://openalex.org/I4210107780"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5037780781","https://openalex.org/A5101443427"],"corresponding_institution_ids":["https://openalex.org/I149594827","https://openalex.org/I4210098460","https://openalex.org/I4210101984","https://openalex.org/I4210107780"],"apc_list":null,"apc_paid":null,"fwci":0.8443,"has_fulltext":false,"cited_by_count":6,"citation_normalized_percentile":{"value":0.78311845,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":97},"biblio":{"volume":"33","issue":"2","first_page":"331","last_page":"347"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11063","display_name":"Rough Sets and Fuzzy Logic","score":0.9995999932289124,"subfield":{"id":"https://openalex.org/subfields/1703","display_name":"Computational Theory and Mathematics"},"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/T11063","display_name":"Rough Sets and Fuzzy Logic","score":0.9995999932289124,"subfield":{"id":"https://openalex.org/subfields/1703","display_name":"Computational Theory and Mathematics"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7020143866539001},{"id":"https://openalex.org/keywords/weighted-sum-model","display_name":"Weighted sum model","score":0.6259515881538391},{"id":"https://openalex.org/keywords/rough-set","display_name":"Rough set","score":0.6183677315711975},{"id":"https://openalex.org/keywords/optimal-decision","display_name":"Optimal decision","score":0.5514972805976868},{"id":"https://openalex.org/keywords/decision-model","display_name":"Decision model","score":0.5104286074638367},{"id":"https://openalex.org/keywords/decision-rule","display_name":"Decision rule","score":0.478672593832016},{"id":"https://openalex.org/keywords/dominance-based-rough-set-approach","display_name":"Dominance-based rough set approach","score":0.4493381381034851},{"id":"https://openalex.org/keywords/decision-problem","display_name":"Decision problem","score":0.4481830894947052},{"id":"https://openalex.org/keywords/mathematical-optimization","display_name":"Mathematical optimization","score":0.35381513833999634},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.3277483582496643},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.3265115022659302},{"id":"https://openalex.org/keywords/decision-tree","display_name":"Decision tree","score":0.3015666902065277},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.2912942171096802},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.19884389638900757}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7020143866539001},{"id":"https://openalex.org/C188222737","wikidata":"https://www.wikidata.org/wiki/Q7979909","display_name":"Weighted sum model","level":4,"score":0.6259515881538391},{"id":"https://openalex.org/C111012933","wikidata":"https://www.wikidata.org/wiki/Q3137210","display_name":"Rough set","level":2,"score":0.6183677315711975},{"id":"https://openalex.org/C150325174","wikidata":"https://www.wikidata.org/wiki/Q4335500","display_name":"Optimal decision","level":3,"score":0.5514972805976868},{"id":"https://openalex.org/C59594135","wikidata":"https://www.wikidata.org/wiki/Q5249242","display_name":"Decision model","level":2,"score":0.5104286074638367},{"id":"https://openalex.org/C84839998","wikidata":"https://www.wikidata.org/wiki/Q5249245","display_name":"Decision rule","level":2,"score":0.478672593832016},{"id":"https://openalex.org/C39105242","wikidata":"https://www.wikidata.org/wiki/Q5290286","display_name":"Dominance-based rough set approach","level":3,"score":0.4493381381034851},{"id":"https://openalex.org/C115988155","wikidata":"https://www.wikidata.org/wiki/Q3262192","display_name":"Decision problem","level":2,"score":0.4481830894947052},{"id":"https://openalex.org/C126255220","wikidata":"https://www.wikidata.org/wiki/Q141495","display_name":"Mathematical optimization","level":1,"score":0.35381513833999634},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.3277483582496643},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.3265115022659302},{"id":"https://openalex.org/C84525736","wikidata":"https://www.wikidata.org/wiki/Q831366","display_name":"Decision tree","level":2,"score":0.3015666902065277},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.2912942171096802},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.19884389638900757}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1080/0952813x.2020.1744195","is_oa":true,"landing_page_url":"https://doi.org/10.1080/0952813x.2020.1744195","pdf_url":"https://www.tandfonline.com/doi/pdf/10.1080/0952813X.2020.1744195?needAccess=true","source":{"id":"https://openalex.org/S153467142","display_name":"Journal of Experimental & Theoretical Artificial Intelligence","issn_l":"0952-813X","issn":["0952-813X","1362-3079"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310320547","host_organization_name":"Taylor & Francis","host_organization_lineage":["https://openalex.org/P4310320547"],"host_organization_lineage_names":["Taylor & Francis"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Journal of Experimental &amp; Theoretical Artificial Intelligence","raw_type":"journal-article"}],"best_oa_location":{"id":"doi:10.1080/0952813x.2020.1744195","is_oa":true,"landing_page_url":"https://doi.org/10.1080/0952813x.2020.1744195","pdf_url":"https://www.tandfonline.com/doi/pdf/10.1080/0952813X.2020.1744195?needAccess=true","source":{"id":"https://openalex.org/S153467142","display_name":"Journal of Experimental & Theoretical Artificial Intelligence","issn_l":"0952-813X","issn":["0952-813X","1362-3079"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310320547","host_organization_name":"Taylor & Francis","host_organization_lineage":["https://openalex.org/P4310320547"],"host_organization_lineage_names":["Taylor & Francis"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Journal of Experimental &amp; Theoretical Artificial Intelligence","raw_type":"journal-article"},"sustainable_development_goals":[{"score":0.7699999809265137,"id":"https://metadata.un.org/sdg/3","display_name":"Good health and well-being"}],"awards":[{"id":"https://openalex.org/G3476242748","display_name":null,"funder_award_id":"71571090","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"}],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"}],"has_content":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W3016056490.pdf","grobid_xml":"https://content.openalex.org/works/W3016056490.grobid-xml"},"referenced_works_count":36,"referenced_works":["https://openalex.org/W1564232874","https://openalex.org/W1704544815","https://openalex.org/W1963531044","https://openalex.org/W1989180336","https://openalex.org/W1989299419","https://openalex.org/W1989650282","https://openalex.org/W2001692054","https://openalex.org/W2011720606","https://openalex.org/W2026819764","https://openalex.org/W2038190934","https://openalex.org/W2043834227","https://openalex.org/W2045986146","https://openalex.org/W2080797159","https://openalex.org/W2095555298","https://openalex.org/W2115200200","https://openalex.org/W2134424860","https://openalex.org/W2137618288","https://openalex.org/W2289935813","https://openalex.org/W2315643593","https://openalex.org/W2515748156","https://openalex.org/W2576122577","https://openalex.org/W2604308625","https://openalex.org/W2699869760","https://openalex.org/W2763102103","https://openalex.org/W2766694548","https://openalex.org/W2772794611","https://openalex.org/W2800217569","https://openalex.org/W2801786879","https://openalex.org/W2803341335","https://openalex.org/W2890144670","https://openalex.org/W2895504516","https://openalex.org/W2914676799","https://openalex.org/W2997864005","https://openalex.org/W4241945909","https://openalex.org/W4255190600","https://openalex.org/W4255833381"],"related_works":["https://openalex.org/W3014464721","https://openalex.org/W155622084","https://openalex.org/W2365612261","https://openalex.org/W1979092190","https://openalex.org/W32032250","https://openalex.org/W4230741605","https://openalex.org/W1561218479","https://openalex.org/W2536793404","https://openalex.org/W2371766315","https://openalex.org/W2377987760"],"abstract_inverted_index":{"In":[0],"order":[1],"to":[2,5,145,150],"actively":[3],"respond":[4],"the":[6,10,46,56,92,99,108,112,127,133,140,146,152,159,166,169,176,184],"severe":[7],"situation":[8],"of":[9,48,91,111,123,137,158,187],"current":[11],"African":[12],"swine":[13],"fever":[14],"(ASF)":[15],"epidemic,":[16],"this":[17,163],"paper":[18],"proposed":[19,181],"a":[20,30,63,71,121],"double-quantitative":[21,31,72],"decision":[22,32,66,73,94,114,129,148,171],"rough":[23,33,64,74],"set":[24,34,75],"method":[25,77,122],"over":[26,36,78,104],"two":[27,37,79,105],"universes.":[28],"First,":[29],"model":[35,119,142,160],"universes":[38,80],"based":[39,81,131,182],"on":[40,82,132,183],"compatibility":[41],"relation":[42],"is":[43,60,116,143],"defined.":[44],"Furthermore,":[45],"characteristics":[47],"ASF":[49,57,83,93,113,124,147,178],"decision-making":[50,58,84,125],"problems":[51],"are":[52,96,180],"fully":[53],"considered,":[54],"and":[55,88,107,126,155],"process":[59,154],"transformed":[61],"into":[62],"approximation":[65,102],"problem.":[67],"Then,":[68],"we":[69],"construct":[70],"application":[76,153,185],"problems.":[85],"The":[86,118],"upper":[87],"lower":[89],"approximations":[90],"objects":[95],"calculated":[97],"by":[98],"double":[100],"quantification":[101],"space":[103],"universes,":[106],"positive":[109],"region":[110],"object":[115],"given.":[117],"proposes":[120],"optimal":[128],"rules":[130],"personal":[134],"preference":[135],"information":[136],"decision-makers.":[138],"Finally,":[139],"theoretical":[141],"applied":[144],"problem":[149,179],"illustrate":[151],"its":[156],"effectiveness":[157],"constructed":[161],"in":[162],"paper.":[164],"At":[165],"same":[167],"time,":[168],"corresponding":[170],"suggestions":[172],"for":[173],"dealing":[174],"with":[175],"actual":[177],"results":[186],"numerical":[188],"examples.":[189]},"counts_by_year":[{"year":2023,"cited_by_count":4},{"year":2022,"cited_by_count":1},{"year":2021,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
